Structural characteristic extraction using drone-generated 3D image data

ABSTRACT

A structural analysis computing device may generate a proposed insurance claim and/or generate a proposed insurance quote for an object pictured in a three-dimensional (3D) image. The structural analysis computing device may be coupled to a drone configured to capture exterior images of the object. The structural analysis computing device may include a memory, a user interface, an object sensor configured to capture the 3D image, and a processor in communication with the memory and the object sensor. The processor may access the 3D image including the object, and analyze the 3D images to identify features of the object—such as by inputting the 3D image into a trained machine learning or pattern recognition program. The processor may generate a proposed claim form for a damaged object and/or a proposed quote for an uninsured object, and display the form to a user for their review and/or approval.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to co-pending U.S. Ser. No. 15/245,529,filed Aug. 24, 2016; U.S. Ser. No. 15/245,659, filed Aug. 24, 2016; U.S.Ser. No. 15/245,687, filed Aug. 24, 2016; and U.S. Ser. No. 15/245,778,filed Aug. 24, 2016, and claims the benefit of priority to U.S.Provisional Patent Application No. 62/266,454, filed Dec. 11, 2015; U.S.Provisional Patent Application No. 62/290,215, filed Feb. 2, 2016; U.S.Provisional Patent Application No. 62/290,233, filed Feb. 2, 2016; andU.S. Provisional Patent Application No. 62/299,658, filed Feb. 25, 2016,the contents of each are hereby incorporated by reference, in theirentirety and for all purposes, herein.

FIELD OF THE INVENTION

The present disclosure relates to photogrammetry and, more particularly,to network-based systems and methods for extracting structuralcharacteristics of structures, rooms, objects, and/or features fromthree-dimensional images captured on a structural analysis computingdevice, and using extracted characteristics to generate insurance quotesand process insurance claims.

BACKGROUND

When a person wishes to insure an insurable asset, such a home orvehicle, against damage, the person may request a quote for an insurancepolicy. The insurance policy may be designed to disburse a claim amountto an owner of the insurance policy when the asset is damaged. Theamount of the claim disbursement paid to the owner may correspond to anamount of damage, a nature of the damage, and/or an estimated cost torepair the damage, compared to a pre-insured value of the object (or avalue of the object established during a quote process before theinsurance policy is purchased). Accordingly, an agent of the associatedinsurance provider (e.g., an underwriter) may need to assess the objectinitially for its value and, subsequent to any damage, assess thedamage. The underwriter may need to photograph, sketch, and/or otherwiserecord the status of the object, as well as any visible pre-insureddamage. This recording process may be time-consuming and frustrating tothe person requesting the quote.

When the object is damaged, an amount of the claim disbursement paid tothe owner of the insurance policy, as quoted, may correspond to anamount of damage, a nature of the damage, and/or an estimated cost torepair the damage. Accordingly, an agent of the associated insuranceprovider (e.g., a claims handler) may travel to the damaged home toassess the damage. The claims handler may sketch an illustration, suchas a floor plan view, of each room that sustained damage. The sketchingprocess may require that the claims handler manually obtain and recordall necessary measurements of the room, then document (e.g., by takingphotos) the room, including all damaged areas. The claims handler mayadditionally need to manually determine and document building materialsand/or the nature of the damage.

At least some known systems permit the claims handler to manually inputall documented data into a software platform configured to prepare anestimate for the claims disbursement (e.g., an estimate of a cost torepair the damage). For example, the claims handler may need to uploadany photos, upload any sketches, manually enter room measurements, andmanually enter any addition details (e.g., room name, room type,building materials, etc.). In addition, at least some known insurancesoftware platforms may require the claims handler to generate newprojects, manually enter information associated with an existingproject, and/or manually enter information for each separate damagedroom in a single project. Needless to say, the entire process may betime-consuming and laborious for the claims handler. Moreover, thelonger the process takes for the claims handler, the longer it may takefor the homeowner to receive their claim disbursement, which isdisadvantageous for the homeowner and may lead to frustration.Conventional methods may also have drawbacks associated with determiningappropriate insurance coverages and accurate claim assessment, and/orother drawbacks. Any reduction in the time and/or labor involved in theclaims handling process may be desirable.

BRIEF SUMMARY

The present embodiments may relate to systems and methods for capturingand analyzing three-dimensional (3D) images using mobile photogrammetry.A mobile photogrammetry system, as described herein, may include astructural analysis computing device that includes an object sensorconfigured to capture 3D images of a structure, room, object, and/orfeature (collectively referred to herein as “object”). The object sensormay be configured to capture 3D images of the object and communicatethose images to the structural analysis computing device for furtherprocessing. The structural analysis computing device may be configuredto implement various software applications or platforms to analyze thecaptured 3D images, and may be configured to use the analysis thereof togenerate one of more insurance quotes associated with the object and/orgenerate, update, and/or handle claims on an insurance policy associatedwith the object.

In one aspect, a structural analysis computing device for generating aninsurance claim for an object pictured in a three-dimensional (3D) imagemay be provided. The structural analysis computing device may be coupledto a drone. The structural analysis computing device may include amemory, a user interface, an object sensor configured to capture the 3Dimage of the object, and at least one processor in communication withthe memory and the object sensor. The at least one processor may beprogrammed to transmit an instruction to the drone to navigate to theobject, and transmit an instruction to the object sensor to capture the3D image of the object. The at least one processor may also beprogrammed to access the 3D image of the object, analyze the 3D image toidentify features of the object, and determine a nature and an extent ofdamage to a damaged feature of the object. The at least one processormay be further programmed to determine a cost of repair of the damagedfeature of the object based upon the nature and extent of the damage,generate a claim form including the determined cost of repair, anddisplay the generated claim form to a user of the structural analysiscomputing device for review and approval by the user. The structuralanalysis computing device may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

In another aspect, a computer-implemented method for generating aninsurance claim for an object pictured in a three-dimensional (3D) imagemay be provided. The method may be implemented using a structuralanalysis computing device including a memory, a user interface, anobject sensor configured to capture the 3D image of the object, and atleast one processor in communication with the memory and the objectsensor. The structural analysis computing device may be coupled to adrone. The method may include transmitting an instruction to the droneto navigate to the object, and transmitting an instruction to the objectsensor to capture the 3D image of the object. The method may alsoinclude accessing the 3D image including the object, analyzing the 3Dimages to identify features of the object, and determining a nature andan extent of damage to a damaged feature of the object. The method mayfurther include determining a cost of repair of the damaged feature ofthe object based upon the nature and extent of the damage, generating aclaim form including the determined cost of repair, and displaying thegenerated claim form to a user of the structural analysis computingdevice for review and approval by the user. The method may includeadditional, less, or alternate actions, including those discussedelsewhere herein.

In a further aspect, a mobile photogrammetry system for generating aninsurance claim associated with an object pictured in athree-dimensional (3D) image may be provided. The mobile photogrammetrysystem may include a structural analysis computing device coupled to adrone, and an insurance server. The structural analysis computing devicemay include a first memory, an object sensor configured to capture the3D image of the object, and at least one first processor incommunication with the first memory and the object sensor. The at leastone first processor may be programmed to transmit an instruction to thedrone to navigate to the object, transmit an instruction to the objectsensor to capture the 3D image of the object, and transmit the 3D imageto the insurance server. The insurance server may include a secondmemory, and at least one second processor in communication with thesecond memory. The at least one second processor may be programmed toreceive the 3D image of the object, and analyze the 3D image to identifyfeatures of the object. The at least one second processor may also beconfigured to determine a nature and an extent of damage to a damagedfeature of the object, and determine a cost of repair of the damagedfeature of the object based upon the nature and extent of the damage.The at least one second processor may be further programmed to generatea claim form including the determined cost of repair, and transmit thegenerated claim form to a user of the structural analysis computingdevice for review and approval by the user. The mobile photogrammetrysystem may include additional, less, or alternate functionality,including that discussed elsewhere herein.

In yet another aspect, a structural analysis computing device forgenerating an insurance quote for an object pictured in athree-dimensional (3D) image may be provided. The structural analysiscomputing device may be coupled to a drone. The structural analysiscomputing device may include a memory, a user interface, an objectsensor configured to capture the 3D image of the object, and at leastone processor in communication with the memory and the object sensor.The at least one processor may be programmed to transmit an instructionto the drone to navigate to the object, and transmit an instruction tothe object sensor to capture the 3D image of the object. The at leastone processor may also be programmed to access the 3D image of theobject, analyze the 3D image, and determine a value of the object basedupon the analysis. The at least one processor may be further programmedto generate a quote associated with the object based upon the determinedvalue of the object, and transmit the quote for display at a usercomputing device to facilitate providing insurance coverage based upon3D image data. The structural analysis computing device may includeadditional, less, or alternate functionality, including that discussedelsewhere herein.

In a still further aspect, a computer-implemented method for generatinga quote associated with an object pictured in a three-dimensional (3D)image may be provided. The method may include transmitting, using atleast one processor of a structural analysis computing device mounted toa drone, an instruction to the drone to navigate to the object. Themethod may also include transmitting, using the at least one processor,an instruction to an object sensor of the structural analysis computingdevice to capture the 3D image of the object, and accessing, using theat least one processor, the 3D image of the object. The method mayfurther include analyzing, using the at least one processor, theaccessed 3D image, and determining, using the at least one processor, avalue of the object based upon the analysis. The method may stillfurther include generating, using the at least one processor, a quoteassociated with the object based upon the determined value of theobject, and transmitting, using the at least one processor, the quotefor display at a user computing device to facilitate providing insurancecoverage based upon 3D image data. The method may include additional,less, or alternate actions, including those discussed elsewhere herein.

In another aspect, a mobile photogrammetry system for generating a quoteassociated with an object pictured in a three-dimensional (3D) image maybe provided. The mobile photogrammetry system may include a structuralanalysis computing device coupled to a drone and insurance server. Thestructural analysis computing device may include a first memory, anobject sensor configured to capture the 3D image of the object, and atleast one first processor in communication with the first memory and theobject sensor. The at least one first processor may be programmed totransmit an instruction to the drone to navigate to the object, transmitan instruction to the object sensor to capture the 3D image of theobject, and transmit the 3D image to the insurance server. The insuranceserver may include a second memory, and at least one second processor incommunication with the second memory. The at least one second processormay be programmed to receive the 3D image of the object, analyze thereceived 3D image, and determine a value of the object (such as anactual value, or repair or replacement cost) based upon the analysis.The at least one second processor may also be programmed to generate aquote associated with the object based upon the determined value of theobject, and transmit the quote for display at a user computing device tofacilitate providing insurance coverage based upon 3D image data. Themobile photogrammetry system may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

In one aspect, an insurance server (or computer system) for generating aquote associated with an object pictured in a three-dimensional (3D)image may be provided. The insurance server may include a processor incommunication with a memory. The at least one processor may beprogrammed to receive the 3D image including the object from astructural analysis computing device, and analyze the received 3D image.The at least one processor may also be programmed to determine a valueof the object based upon the analysis, and generate a quote associatedwith the object based upon the determined value of the object. The atleast one processor may be further programmed to transmit the quote fordisplay at the structural analysis computing device to facilitateproviding insurance based upon 3D image data. The server or computersystem may include additional, less, or alternate functionalityincluding that discussed elsewhere herein.

In another aspect, a computer-implemented method for generating a quoteassociated with an object pictured in a three-dimensional (3D) image maybe provided. The method may be implemented using an insurance serverincluding a processor in communication with a memory. The method mayinclude receiving the 3D image including the object from a structuralanalysis computing device, and analyzing the received 3D image. Themethod may also include determining a value of the object based upon theanalysis, and generating a quote associated with the object based uponthe determined value of the object. The method may further includetransmitting the quote for display at the structural analysis computingdevice. The method may include additional, less, or alternate actions,including those discussed elsewhere herein, and may be implemented viaone or more local or remote processors.

In yet another aspect, at least one non-transitory computer-readablestorage media having computer-executable instructions embodied thereonmay be provided. When executed by an insurance server including at leastone processor in communication with a memory, the computer-executableinstructions may cause the at least one processor to receive a 3D imageincluding an object from a structural analysis computing device, andanalyze the received 3D image. The computer-executable instructions mayalso cause the at least one processor to determine a value of the objectbased upon the analysis, and generate a quote associated with the objectbased upon the determined value of the object. The computer-executableinstructions may further cause the at least one processor to transmitthe quote for display at the structural analysis computing device. Theinstructions may direct additional, less, or alternate functionality,including that discussed elsewhere herein.

In one aspect, a structural analysis computing device (or computersystem) for generating an insurance claim for an object pictured in athree-dimensional (3D) image may be provided. The structural analysiscomputing device may include a memory, a user interface, an objectsensor configured to capture the 3D image of the object, and at leastone processor in communication with the memory and the object sensor.The at least one processor may be programmed to access the 3D imageincluding the object, and analyze the 3D images to identify features ofthe object. The at least one processor may also be configured todetermine a nature and an extent of damage to a damaged feature of theobject, and determine a cost of repair of the damaged feature of theobject based upon the nature and extent of the damage. The at least oneprocessor may be further configured to generate a claim form includingthe determined cost of repair, and display the generated claim form to auser of the structural analysis computing device. As a result, proposedvirtual insurance claims may be presented to insureds for their reviewand/or approval. The structural analysis computing device (or computersystem) may include additional, less, or alternate functionality,including that discussed elsewhere herein.

In another aspect, a computer-implemented method for generating aninsurance claim for an object pictured in a three-dimensional (3D) imagemay be provided. The method may be implemented using a structuralanalysis computing device including a memory, a user interface, anobject sensor configured to capture the 3D image of the object, and atleast one processor in communication with the memory and the objectsensor. The method may include accessing the 3D image including theobject, and analyzing the 3D images to identify features of the object.The method may also include determining a nature and an extent of damageto a damaged feature of the object, and determining a cost of repair ofthe damaged feature of the object based upon the nature and extent ofthe damage. The method may further include generating a claim formincluding the determined cost of repair, and displaying the generatedclaim form to a user of the structural analysis computing device fortheir review and/or approval. The method may include additional, less,or alternate actions, including that discussed elsewhere herein.

In a further aspect, at least one non-transitory computer-readablestorage media having computer-executable instructions embodied thereonmay be provided. When executed by a structural analysis computing deviceincluding a memory, a user interface, an object sensor configured tocapture a 3D image of an object, and at least one processor incommunication with the memory and the object sensor, thecomputer-executable instructions may cause the at least one processor toaccess the 3D image including the object, and analyze the 3D images toidentify features of the object. The computer-executable instructionsmay also cause the at least one processor to determine a nature and anextent of damage to a damaged feature of the object, and determine acost of repair of the damaged feature of the object based upon thenature and extent of the damage. The computer-executable instructionsmay further cause the at least one processor to generate a claim formincluding the determined cost of repair, and display the generated claimform to a user of the structural analysis computing device. Thecomputer-executable instructions may include or direct additional, less,or alternate functionality, including that discussed elsewhere herein.

Advantages will become more apparent to those skilled in the art fromthe following description of the preferred embodiments which have beenshown and described by way of illustration. As will be realized, thepresent embodiments may be capable of other and different embodiments,and their details are capable of modification in various respects.Accordingly, the drawings and description are to be regarded asillustrative in nature and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

The Figures described below depict various aspects of the systems andmethods disclosed therein. It should be understood that each Figuredepicts an embodiment of a particular aspect of the disclosed systemsand methods, and that each of the Figures is intended to accord with apossible embodiment thereof. Further, wherever possible, the followingdescription refers to the reference numerals included in the followingFigures, in which features depicted in multiple Figures are designatedwith consistent reference numerals.

There are shown in the drawings arrangements which are presentlydiscussed, it being understood, however, that the present embodimentsare not limited to the precise arrangements and are instrumentalitiesshown, wherein:

FIG. 1 depicts a schematic view of an exemplary mobile photogrammetrycomputer system;

FIG. 2 depicts a schematic view of an exemplary structural analysiscomputing device used in the mobile photogrammetry system shown in FIG.1;

FIG. 3 depicts a first exemplary use of the mobile photogrammetry systemshown in FIG. 1 including a user using the structural analysis computingdevice shown in FIG. 2 to capture three-dimensional (3D) images of astructure for analysis;

FIG. 4 depicts an exemplary user interface of a structural analysissoftware platform implemented on the structural analysis computingdevice shown in FIG. 2;

FIG. 5 depicts an exemplary embodiment of the structural analysissoftware platform implemented on the structural analysis computingdevice shown in FIG. 2 extracting additional measurements;

FIG. 6 depicts a 3D model of the structure being analyzed using themobile photogrammetry system shown in FIG. 1;

FIG. 7 depicts a second exemplary use of the mobile photogrammetrysystem shown in FIG. 1 including a first 3D image of a room;

FIG. 8 depicts a second 3D image of the room shown in FIG. 7;

FIG. 9 illustrates a third exemplary use of the mobile photogrammetrysystem shown in FIG. 1;

FIG. 10 illustrates an exemplary data file used in the mobilephotogrammetry system shown in FIG. 1;

FIG. 11 depicts an exemplary configuration of a server computing devicethat may be used in the mobile photogrammetry system shown in FIG. 1;

FIG. 12 illustrates a flowchart of an exemplary computer-implementedmethod for extracting structural characteristics of a structure usingthe mobile photogrammetry system shown in FIG. 1;

FIG. 13 depicts a diagram of components of one or more exemplarycomputing devices that may be used in the mobile photogrammetry systemshown in FIG. 1;

FIG. 14 depicts a schematic view of a first alternative embodiment of amobile photogrammetry computer system;

FIG. 15 depicts an exemplary computer-implemented method of estimatingrepair and/or replacement costs for insured assets using 3D data;

FIG. 16 depicts another exemplary computer-implemented method ofestimating repair and/or replacement costs for insured assets using 3Ddata;

FIG. 17 illustrates a block diagram of an exemplary mobilephotogrammetry system including a structural analysis computing devicemounted to a drone;

FIG. 18 illustrates a side view of a neighborhood that may be analyzedby the exemplary system shown in FIG. 17; and

FIG. 19 illustrates a cross-sectional side view of a building that maybe analyzed by the exemplary system shown in FIG. 17.

The Figures depict preferred embodiments for purposes of illustrationonly. One skilled in the art will readily recognize from the followingdiscussion that alternative embodiments of the systems and methodsillustrated herein may be employed without departing from the principlesof the invention described herein.

DETAILED DESCRIPTION OF THE DRAWINGS

The present embodiments may relate to, inter alia, systems and methodsfor extracting structural characteristics of a structure usingthree-dimensional (3D) images, for example, using photogrammetry.Photogrammetry refers to the use of photography to measure distancesbetween or features of objects. The mobile photogrammetry systemdescribed herein may include a structural analysis computing deviceconfigured to perform automatic analysis of the 3D images. Thestructural analysis computing device may include an object sensor and atleast one processor in communication with a memory. The object sensor,which may be integral to and/or coupled to the structural analysiscomputing device, is configured to capture one or more 3D images of theobject (e.g., a building, a home, a room, and/or feature thereof).

The structural analysis computing device may be configured to implementa structural analysis software platform to automatically analyze thecaptured 3D images, as described herein. The structural analysiscomputing device may be further configured to implement a claimevaluation software platform to evaluate the analyzed images forinsurance claim disbursement purposes. In some embodiments, the memorymay include one or more storage devices, including cloud storagedevices, internal memory devices, non-centralized databases, and/orcombinations thereof.

In addition, although the analysis and evaluation are described hereinas being performed by a single computing device, it should be understoodthat more than one computing device may perform the various actions andsteps described herein. For example, the structural analysis softwareplatform may be implemented by one computing device and the claimevaluation software platform may be implemented by another computingdevice without departing from the scope of the present disclosure.

In one exemplary embodiment, a user (e.g., a homeowner or other userassociated with the structure, a claims handler, etc.) may access astructural analysis software application or platform on their structuralanalysis computing device. The structural analysis software platform mayinclude 3D photogrammetry capability. The structural analysis computingdevice may include, for example, a mobile phone, a smart phone, atablet, a laptop computer, a dedicated structural analysis computingdevice, etc. In one exemplary embodiment, the structural analysiscomputing device may be a mobile computing device, such that thestructural analysis computing device may be relatively easilytransported to the structure(s) being analyzed and relatively easilymaneuvered and manipulated within the structure(s). In one exemplaryembodiment, the structural analysis computing device may be mounted to,integral to, and/or otherwise coupled to a drone. Accordingly, the usermay access additional spaces than were previously accessible, such as aroof or attic space, for analysis thereof (e.g., to assess damage to astructure).

Accordingly, the structural analysis software platform may be configuredto analyze 3D images of a structure, rooms therein, features thereof,and/or contents therein. For example, the structural analysis softwareplatform may be configured to analyze 3D images of buildings, rooms,vehicles, objects (e.g., televisions, appliances, etc.), people,inventories, and/or other suitable subjects, as described furtherherein.

The user may input a number of elements into the structural analysissoftware platform to initialize, describe, and/or identify the subjectof the images to be captured and analyzed. The structural analysissoftware platform may prompt such input, for example, by displayingfields (e.g., text fields, drop-down lists, selection boxes, etc.)labelled to request particular information from the user. For example,in one case in which the user is capturing images of a room as part of aclaims submission and/or handling process, the user may input anidentification of an object. An “object” may refer to any subject of animage, such as a structure, (e.g., a home or other building), a room(e.g., a living room, kitchen, etc.), and/or a particular feature thatmay have been damaged.

In other words, the user may input project identifier(s), roomidentifier(s), and/or claim identifier(s). This information may includea claim number, a policy number of an insurance policy associated withthe structure and/or the user, a policyholder name or other identifier,a room type, room features (e.g., ceiling type, window type, door type,staircase, building materials, etc.), location of damage, and/or anyother required (e.g., by the structural software platform) orrecommended data.

The user may then use the object sensor coupled to and/or integral totheir structural analysis computing device, as described herein, tocapture one or more 3D images of the object, of interest (e.g., thestructure, room, object, and/or feature that has been damaged and forwhich a claim is being submitted and/or handled). The user may captureone or more 3D images, for example, at different angles, at differentdistances from a feature or room, and/or at different orientations(e.g., landscape, portrait, horizontal, vertical, panorama, etc.), inorder to capture an entirety of the structure, room, object, and/orfeature of interest.

The structural analysis platform may be configured to analyze thecaptured 3D images. Such analysis may include automatically extractingwall-to-wall (i.e., wall length) and/or ceiling-to-floor (i.e., wallheight) measurements of the room. In some embodiments, the structuralanalysis software platform may be configured to automatically extractadditional measurements, for example, of doorways, windows, missing walllengths, missing wall heights, and/or other features.

Additionally or alternatively, as described further herein, the user mayinstruct the structural analysis software platform to extract additionalmeasurements. The structural analysis software platform may beconfigured to display one or more of the 3D image(s) on a display device(e.g., screen) of the structural analysis computing device. In theexemplary embodiment, the structural analysis software platform may beconfigured to display one or more of the automatically extractedmeasurements on the displayed 3D image(s) for review.

The user may then review the displayed 3D images including theautomatically extracted (e.g., wall-to-wall and/or ceiling-to-floor)measurements. The structural analysis software platform may facilitatedisplay of the 3D images to the user such that user may manipulate thedisplayed 3D images. For example, the user may rotate the 3D image, mayzoom in, and/or may zoom out to change a displayed view. In someembodiments, the user may determine that additional measurements areneeded in order to fully analyze or assess the damage to the structure.For example, the user may determine that a particular feature of theroom, such as a set of cabinetry or a bay of windows, needs repair orreplacement. Accordingly, the damaged feature(s) may need to be measuredin order to accurately generate an estimated repair or replacement cost(e.g., a claim disbursement amount).

The user may instruct the structural analysis software platform toextract any additional measurements. The structural analysis softwareplatform may be configured to receive user input from the user from aninput device of the structural analysis computing device (e.g., a mouse,keyboard, touch screen interface, etc.). The user may use the inputdevice to input the instructions to extract the additional measurements.In one exemplary embodiment, the structural analysis software platformmay accept “point and click” input. More specifically, the user mayselect a particular distance to be measured by selecting (e.g.,clicking, tapping, hovering over, etc.) a first input location on thedisplayed 3D image corresponding to a first end of the desiredadditional measurement. This first input location received by thestructural analysis software platform from the input device mayrepresent a first physical location, such as the physical location of afirst end of the set of cabinets or a first end of the bay of windows.The user may then select a second input location on the displayed 3Dimage, spaced apart from the first input location, corresponding to asecond end of the desired additional measurement. This second inputlocation received by the structural analysis software platform from theinput device may represent a second physical location, such as thephysical location of a second end of the set of cabinets of a second endof the bay of windows. The structural analysis software platform maythen determine a first distance between the first and second inputlocations, and, accordingly, extract a second distance corresponding tothe physical distance between the first and second physical locations.This second distance may be displayed as the requested additionalmeasurement.

The user may request any number of additional measurements. Inalternative embodiments, the structural analysis software platform mayaccept instructions to extract additional measurements according to anyother method, for example, using pixel coordinates or an alternativesyntax to input opposing ends of the requested additional measurements.Once the user is satisfied that any necessary measurements have beenextracted, the user may instruct the structural analysis softwareplatform to complete the user input process and export the image and anyextracted measurements. For example, the user may select a “Complete andExport” command on a user interface of the structural analysis softwareplatform.

The structural analysis software platform may be configured to generatea data file including the 3D image(s) and any extracted measurements. Inone exemplary embodiment, the generated data file is formatted as anExtensible Markup Language (XML) data file. The data file may includeany other data input by the user and/or extracted by the structuralanalysis software platform, including any claim, structure, and/or roomidentifiers, comments, features, objects, building materials, and/or anyother data.

The structural analysis software platform may be configured to exportthe data file. Exporting may include storing the data file in a memory,transmitting the data file to another software platform, and/ortransmitting the data file to another computing device. For example, thestructural analysis software platform may be configured to export thedata file to a claim evaluation software platform installed on and/orimplemented by the structural analysis computing device. The claimevaluation software platform may be configured to use data from the datafile to determine a location, nature, and/or extent of any damage to theobject captured in the 3D image(s).

The claim evaluation software platform may initially review the claim,object, and/or room identifier(s). For example, in one embodiment, theclaim evaluation software platform may be configured to review the claimidentifier to determine whether a project (e.g., a completed or ongoingset of analyses and/or evaluations associated with the claim, object,and/or policyholder) associated with the claim, object, and/orpolicyholder already exists. If no such project exists, the claimevaluation software platform may automatically generate a new projectassociated with at least one of the claim identifier, the objectidentifier, the room identifier, and/or the policyholder. Upongeneration of the new project, the claim evaluation software platformmay automatically review, verify, and/or validate any data in thereceived data file, and may automatically populate any project fieldcorresponding to the data in the received data file.

If a project associated with the claim, object, and/or policyholder doesexist, the claim evaluation software platform may be configured toadditionally determine whether a sub-project associated with the roomidentifier exists. If no such sub-project exists, the claim evaluationsoftware platform may be configured to automatically generate a roomsub-project and automatically populated any sub-project fieldcorresponding to the data in the received data file. If a sub-projectassociated with the room identifier does exist, the claim evaluationsoftware platform may be configured to determine whether the data filecontains any new and/or conflicting information from the data in theexisting sub-project. The claim evaluation software platform may updateany sub-project fields corresponding to the new and/or conflictinginformation.

Upon automatic generation of any new project and/or sub-project, theclaim evaluation software platform may be configured to store theproject and/or sub-project in a memory. In one embodiment, the memoryincludes a cloud storage memory device such that the project and/orsub-project may be accessed by multiple parties and/or from multiplelocations. In some embodiments, when the claim evaluation softwareplatform updates an existing project and/or sub-project with new orupdated data, the claim evaluation software platform may be configuredto store the updated project and/or sub-project in the memory.Additionally or alternatively, the claim evaluation software platformmay be configured to store a record of the update in the memory.

To analyze the data in a project and/or sub-project for claimevaluation, the user may access the claim evaluation software platform,which may be configured to retrieve the corresponding stored projectand/or sub-project from the memory. The user may then instruct the claimevaluation software platform to analyze the data in the project and/orsub-project and generate a claim evaluation. The claim evaluationsoftware platform may be configured to analyze the data to determine alocation, nature, and/or extent of the damage. For example, the claimevaluation software platform may determine that a set of cabinets and acooktop in a kitchen have been damaged in a fire. The claim evaluationsoftware platform may determine that an entire cabinet base must bereplaced, that two cabinet doors must be replaced, and that the cooktopmust be cleaned.

In some embodiments, the user may input certain information into theclaim evaluation software platform to supplement these determinations.For example, the user may input whether the nature of the damagerequires cleaning, repair, replacement, and/or abatement.

In addition, the claim evaluation software platform may be configured toanalyze the 3D images taken and additional information stored in thememory to generate an insurance claim evaluation. The claim evaluationsoftware may be configured to determine an amount of loss (e.g., a claimdisbursement amount) and/or the nature and amount of work (e.g., repair,replacement, abatement, cleaning, etc.) needed to address the claim.Continuing with the same example, the claim evaluation software platformmay be configured to analyze the 3D images to determine that the basecabinets and cabinet doors are fabricated from a particular materialthat carries a particular replacement and/or repair cost. The claimevaluation software platform may use the additional stored informationto further determine an average, typical, expected, minimum, and/ormaximum cost of cooktop cleaning due to fire damage. For example, theclaim evaluation software platform may access a database of materials,costs, past claims, and/or other information to make suchdeterminations.

The claim evaluation software platform may then generate the claimevaluation including a claim disbursement amount based upon the abovedeterminations. The claim evaluation software platform may display theclaim evaluation for review by the user. Additionally or alternatively,the claim evaluation software platform may be configured to transmit theclaim evaluation for review by another party. For example, the mobilecomputing device may transmit the claim evaluation to a third-partycomputing device such as a computing device associated with an insuranceprovider (e.g., a claims computer system). The claim evaluation may bereviewed such that the claim disbursement amount may be transmitted to ahomeowner or other user associated with the damaged structure, room,object, and/or feature.

At least one of the technical problems addressed by this system mayinclude: (i) time-consuming, difficult, and/or laborious manualillustration of structures; (ii) manual measurement of structures,features thereof, and/or contents therein; and/or (iii) inaccessible ornon-intuitive platforms involving manual data entry and/or manipulationand/or manual project generation.

A technical effect of the systems and processes described herein may beachieved by performing at least one of the following steps: (a)transmitting an instruction to a drone to navigate to an object; (b)transmitting an instruction to an object sensor to capture a 3D image ofthe object; (c) accessing the 3D image including the object; (d)analyzing the 3D images to identify features of the object; (e)determining a nature and an extent of damage to a damaged feature of theobject; (f) determining a cost of repair of the damaged feature of theobject based upon the nature and extent of the damage; (g) generating aclaim form including the determined cost of repair; and/or (h)displaying the generated claim form to a user of the structural analysiscomputing device for review and approval by the user. The technicaleffect of the systems and processes described herein may additionallyand/or alternatively be achieved by: (i) determining, using the at leastone processor, a value of the object based upon the analysis; (j)generating, using the at least one processor, a quote associated withthe object based upon the determined value of the object; and/or (k)transmitting, using the at least one processor, the quote for display ata user computing device to facilitate providing insurance coverage basedupon 3D image data.

The technical effect achieved by this system may be at least one of: (i)reduced time and effort in capturing images of structures; (ii)automated and/or simplified measurement of structures using a capturedthree-dimensional image; (iii) automated and/or simplified import andextraction of data necessary to automatically populate and/or generateprojects; (iv) more accurate estimated sizing and/or measurement ofstructures, and thus more accurate risk determination, and/orreplacement or repair cost estimation or determination; (v) improvedspeed in generating, processing, and/or issuing claims and/or claimdisbursements after an insurance claim event; (vi) more accuratereplacement or repair material cost determination and ordering; (vii)improved speed in generating and/or processing insurance quotes; and/or(viii) improved imaging of exterior surfaces of object using dronecapabilities and object sensors configured to function in exteriorlighting.

Exemplary Mobile Photogrammetry Computer System

FIG. 1 depicts a schematic view of an exemplary mobile photogrammetrycomputer system 100. In one exemplary embodiment, system 100 may includeone or more structural analysis computing device(s) 102, 104. Structuralanalysis computing device 102, 104 may be any device capable ofinterconnecting to the Internet including a mobile computing device or“mobile device,” such as a smartphone, a personal digital assistant(PDA), a tablet, a wearable device (e.g., a “smart watch” or a personalprojection device such as “smart glasses”), a “phablet,” or otherweb-connectable equipment or mobile devices. Structural analysiscomputing device 102, 104 may, in some embodiments, be mounted to and/orintegral to a drone. Two structural analysis computing devices 102, 104are shown to exemplify that the processes, methods, steps, and/oractions performed herein, though generally described as being performedon a single structural analysis computing device 102, may be performedmultiple structural analysis computing devices 102, 104. Accordingly,where any functionality is described as being performed by structuralanalysis computing device 102, it should be understood that thefunctionality may be performed in part or in whole by structuralanalysis computing device 104. It should also understood that certainprocesses described herein may be implemented using one structuralanalysis computing device 102, 104 (e.g., capturing 3D image data usinga smartphone or a drone), and other processes described herein may beimplemented using a different computing device, such as anotherstructural analysis computing device 102, 104 or another user computingdevice (e.g., receiving and analyzing the captured data using a tabletor laptop).

Additionally, a database server 106 may be connected to a memory device108 containing information on a variety of matters, as described belowin greater detail. In one exemplary embodiment, memory device 108 mayinclude a cloud storage device, such that information stored thereon maybe accessed by any of structural analysis computing devices 102, 104(and/or an insurance server 112) from any location. In one embodiment,memory device 108 may be stored on structural analysis computing device102, 104. In any alternative embodiment, memory device 108 may be storedremotely from structural analysis computing device 102, 104 and may benon-centralized. Moreover, in any alternative embodiment, memory device108 may be stored on an insurance server 112, as described furtherherein.

In one exemplary embodiment, structural analysis computing device 102may include an object sensor 110, as described further herein. Objectsensor 110 may be coupled to structural analysis computing device 102.In some embodiments, object sensor 110 may be externally attached by abracket, clip, elastic, magnet, and/or adhesive to structural analysiscomputing device 102. In other embodiments, object sensor 110 may beintegral to structural analysis computing device 102, for example,coupled to structural analysis computing device 102 internal to ahousing or case (not shown) of structural analysis computing device 102.Object sensor 110 may be configured to capture one or morethree-dimensional (3D) images of a structure and/or of any othersubject, such a room, object, and/or feature of the structure, and/or,in some embodiments, a person (collectively referred to herein as“object”).

Structural analysis computing device 102 may be configured to implementone or more software platforms, as described further herein, to analyzethe captured 3D images. Structural analysis computing device 102 may befurther configured to generate a data file including the results of thatanalysis and the analyzed 3D images. Structural analysis computingdevice 102 may transmit the data file to memory device 108 for storageand/or for access to the data file by one or more other computingdevices (e.g., structural analysis computing device 104 and/or insuranceserver 112). Structural analysis computing device 102 may be furtherconfigured to use the results of the analysis to perform various otherfunctions. For example, structural analysis computing device mayevaluate the 3D images and/or the analysis thereof in an insuranceclaims generation and/or handling process, to generate an insuranceclaim associated with damage to the object pictured in the 3D images.Structural analysis computing device 102 may be further configured toretrieve reference information from memory device 108 to performanalysis and/or evaluation of any of the above-described information.

In one exemplary embodiment, mobile photogrammetry system 100 mayfurther include an insurance server 112, which may be in communicationwith structural analysis computing device 102, structural analysiscomputing device 104, and/or memory device 108. Insurance server 112 maybe associated with and/or maintained by an insurance provider. Insuranceserver 112 may provide reference information to memory device 108, suchas, for example, policy information (e.g., policy amount, premium,discount) associated with a particular object; historical informationaland/or images associated with a particular object; past claims involvingthe object or a user associated with the object; propriety underwritinginformation associated with the object and/or a corresponding policy;past claims information including past disbursement amount associatedwith particular damage, repair, and/or replacement; and/or other damage,repair, replacement, and/or abatement information including costsassociated therewith.

Additionally or alternatively, insurance server 112 may retrieve anyinformation generated and/or stored by structural analysis computingdevice 102. For example, insurance server 112 may receive the data fileincluding the 3D images and associated analyses thereof, and may storethe data file (e.g., in memory device 108 and/or in another memory, notshown) for future reference. Insurance server 112 may further receive aclaim generated by structural analysis computing device 102. Insuranceserver 112 may use the generated claim to disburse a claim disbursementamount, and/or to update and/or adjust an existing insurance policycorresponding to the claim.

Exemplary Structural Analysis Computing Device

FIG. 2 depicts a schematic view of an exemplary structural analysiscomputing device 102, 104 (as shown in FIG. 1) used in mobilephotogrammetry system 100 (also shown in FIG. 1). Structural analysiscomputing device 102, 104 (referred to herein as “structural analysiscomputing device 102” for simplicity) may include an object sensor 110and at least one processor 202 for executing instructions. In someembodiments, executable instructions may be stored in a memory area 220(which may include and/or be similar to memory device 108, shown in FIG.1). Processor 202 may include one or more processing units (e.g., in amulti-core configuration). Memory area 220 may be any device allowinginformation such as executable instructions and/or other data to bestored and retrieved. Memory area 220 may include one or morecomputer-readable media.

As described above, object sensor 110 may by coupled to and/or integralto structural analysis computing device 102. Object sensor 110 mayinclude at least one infrared light source 204, an infrared lightprojector 206, and/or an infrared camera 208. The at least one infraredlight source 204 may include, for example, one or more infrared LEDsand/or any other suitable infrared light sources. Infrared lightprojector 206 is configured to cast or project light output frominfrared light source(s) 204 in a structured pattern (e.g., as a patternof beams or dots). Infrared camera 208 may include any suitable infraredcamera and/or any components or accessories necessary to transform anexisting camera (not shown) integral to structural analysis computingdevice 102 into an infrared camera (e.g., additional lenses, processingequipment, etc.). Infrared camera 208 may be configured to captureimages including the projected, structured light. By processingvariations in the structured light of these images (e.g., usingprocessor 202 and/or a processor (not shown) included in object sensor110), three-dimensional (3D) images may be generated. Accordingly,object sensor 110 may be able to capture 3D images or models. In someembodiments, object sensor 110 is configured to function in interior ordarker lighting conditions, such as within a home, and/or in exterior,ambient, or brighter lighting conditions, such as around the exterior ofa home.

Processor 202 may be configured to receive these captured 3D images fromobject sensor 110. In addition, processor 202 may be configured todownload, install, and/or implement a plurality of software applicationsor platforms. In one exemplary embodiment, processor 202 is configuredto implement a structural analysis software platform 210 and a claimevaluation software platform 212.

Structural analysis software platform 210 may be configured to processthe received 3D images. Structural analysis software platform 210 mayinclude 3D photogrammetry capability, such that structural analysissoftware platform 210 may process and interpret the dimensionality andfeatures of the 3D images, including detecting types of materials thatthe object(s) of the 3D images are made of and/or an amount of damagethereto. Accordingly, structural analysis software platform 210 may beconfigured to analyze 3D images of an object, such as a structure, roomstherein, features thereof, and/or contents therein (e.g., televisions,appliances, etc., people, inventories, and/or other suitable objects).

Structural analysis software platform 210 may be configured to receive aplurality of data elements to initialize, describe, and/or identify theobject picture in the 3D images. Structural analysis software platform210 may prompt such input, for example, by displaying fields (e.g., textfields, drop-down lists, selection boxes, etc.) labelled to requestparticular information from the user. For example, in one case in whicha user accesses structural analysis software platform 210 as part of aclaims submission and/or handling process, the user may input anidentification of a structure (e.g., a home or other building), a room(e.g., a living room, kitchen, etc.), and/or a particular feature thatmay have been damaged. In other words, structural analysis softwareplatform 210 may receive project identifier(s), room identifier(s),and/or claim identifier(s). This information may include a claim number,a policy number of an insurance policy associated with the structureand/or the user, a policyholder name or other identifier, a room type,room features (e.g., ceiling type, window type, door type, staircase,building materials, etc.), location of damage, and/or any other data.

Structural analysis software platform 210 may be configured to analyzethe captured 3D images. In one exemplary embodiment, structural analysissoftware platform 210 may be configured to automatically extract aplurality of measurements in the 3D images. For example, if the objectpictured in the 3D images is a structure or room, structural analysissoftware platform 210 may be configured to automatically extract one ormore of wall length, wall height, doorway dimension, window dimension,missing wall height, and/or missing wall length.

Structural analysis software platform 210 may be configured to displayone or more of the 3D image(s) on a display device 222 of structuralanalysis computing device 102. Display device 222 may be any componentcapable of conveying information to the user. In some embodiments,display device 222 may include an output adapter such as a video adapterand/or an audio adapter operatively coupled to processor 202. Displaydevice 222 may include, for example, a liquid crystal display (LCD),organic light emitting diode (OLED) display, cathode ray tube (CRT), or“electronic ink” display and/or an audio output device (e.g., a speakeror headphones). In some embodiments, display device 222 may beconfigured to present an interactive user interface (e.g., a web browseror client application) to the user. The interactive user interface mayinclude, for example, a user interface for structural analysis softwareplatform 210 and/or claim evaluation software platform 212.

Stored in memory area 220 are, for example, computer-readableinstructions for providing a user interface to the user via displaydevice 222 and, optionally, receiving and processing input from inputdevice 224. A user interface may include, among other possibilities, aweb browser and client application. Web browsers enable users to displayand interact with media and other information typically embedded on aweb page or a website from a web server associated with a third party(e.g., an insurance provider). A client application allows users tointeract with a server application associated with, for example, avendor or business. In the example embodiment, the structural analysissoftware platform may be configured to display (e.g., on display device222 and/or a user interface thereon) one or more of the automaticallyextracted measurements on the displayed 3D image(s) for review.

The user may then review the displayed 3D images including theautomatically extracted measurements. Structural analysis softwareplatform 210 may facilitate display of the 3D images on display device222 such that user may manipulate the displayed 3D images. For example,the user may rotate the 3D image, may zoom in, and/or may zoom out tochange a displayed view. In some embodiments, the user may determinethat additional measurements are needed in order to fully analyze orassess the object. For example, the user may determine that a particularfeature of a room, such as a set of cabinetry or a bay of windows, needsrepair or replacement. Accordingly, the damaged feature(s) may need tobe measured in order to accurately generate an estimated repair orreplacement cost (e.g., a claim disbursement amount). Structuralanalysis software platform 210 may be configured to extract anyadditional measurements, either automatically or upon request orinstruction from the user of structural analysis computing device 102.

Structural analysis software platform 210 may be configured to receiveuser input from the user from an input device 224 of the structuralanalysis computing device. Input device 224 may include, for example, akeyboard, a pointing device, a mouse, a stylus, a touch sensitive panel(e.g., a touch pad or a touch screen), a camera, a gyroscope, anaccelerometer, a position detector, and/or an audio input device. Itshould be understood that in some embodiment, a single component such asa touch screen may function as both display device 222 and input device224. In one exemplary embodiment, structural analysis software platform210 may accept “point and click” input from the user via input device224.

Structural analysis software platform 210 may receive a first user inputcorresponding to a first input location from input device 224 (e.g.,corresponding to a first end of the desired additional measurement).This first input location may represent a first physical location, suchas the physical location of a first end of the set of cabinets or afirst end of the bay of windows. Structural analysis software platform210 may receive a second user input corresponding to a second inputlocation from input device 224 (e.g., corresponding to a second end ofthe desired additional measurement). This second input location mayrepresent a second physical location, such as the physical location of asecond end of the set of cabinets of a second end of the bay of windows.Structural analysis software platform 210 may then determine a firstdistance between the first and second input locations, and, accordingly,extract a second distance corresponding to the physical distance betweenthe first and second physical locations. Structural analysis softwareplatform 210 may then display the second distance as an additionalmeasurement on the 3D image on display device 222. In alternativeembodiments, structural analysis software platform 210 may acceptinstructions to extract additional measurements according to any othermethod, for example, using pixel coordinates or an alternative syntax toinput opposing ends of the requested additional measurements.

Structural analysis software platform 210 may extract and/or display anynumber of additional measurements. Once the user is satisfied that anynecessary measurements have been extracted, the user may instructstructural analysis software platform 210 to complete this user inputprocess and export the 3D image and any extracted measurements. Forexample, the user may select a “Complete and Export” command on a userinterface of structural analysis software platform 210. Upon receivinginstructions to complete the user input process, structural analysissoftware platform 210 may be configured to generate a data fileincluding the 3D image(s) and any extracted measurements. In oneexemplary embodiment, the generated data file is formatted as anExtensible Markup Language (XML) data file. The data file may includeany other data received and/or extracted by structural analysis softwareplatform 210, including any claim, structure, and/or room identifiers,comments, features, objects, building materials, and/or any other data.

Structural analysis software platform 210 may be configured to exportthe data file. Exporting may include storing the data file in a memory(e.g., memory device 108 and/or memory 220), transmitting the data fileto another software platform, and/or transmitting the data file toanother computing device. For example, structural analysis softwareplatform 210 may be configured to export the data file to claimevaluation software platform 212 installed on and/or implemented byprocessor 202. Structural analysis computing device 102 may also includea communication interface 226, which is communicatively coupleable to aremote device such as another structural analysis computing device 102,104 and/or insurance server 112 (shown in FIG. 1). Communicationinterface 1125 may include, for example, a wired or wireless networkadapter or a wireless data transceiver for use with a mobile phonenetwork (e.g., Global System for Mobile communications (GSM), 3G, 4G orBluetooth) or other mobile data network (e.g., WorldwideInteroperability for Microwave Access (WIMAX)).

Exemplary Use of Mobile Photogrammetry System and Structural AnalysisComputing Device

The following examples are illustrative of various aspects andembodiments of the disclosure described herein. Accordingly, it shouldbe understood that such examples are for illustration only and do notlimit the scope of the present disclosure.

FIGS. 3-6 illustrate various aspects of the disclosure using a firstexample of an object, in this case a structure 302, being analyzed usingthe mobile photogrammetry system 100 shown in FIG. 1. In particular,FIG. 3 depicts a user 300 using a structural analysis computing device102 (as shown in FIGS. 1 and 2) to capture three-dimensional (3D) imagesof structure 302 for analysis. Structure 302 includes a first room 304,which itself includes a plurality of walls 306 and windows 308. In theexemplary embodiment, structural analysis computing device 102 isillustrated as a tablet, however, it should be understood thatstructural analysis computing device 102 may be any structural analysiscomputing device configured to function as described herein.

User 300 may capture one or more 3D images of structure 302. Inparticular, user 300 may capture a plurality of 3D images of room 304,and a plurality of 3D images of any other room(s) of interest instructure 302. For example, user 300 may be a homeowner of structure 302submitting 3D images for a claim for broken windows 310, 312 and adamaged portion 316 of a floor 314 of room 304, and/or may be a claimshandler capturing 3D images for that claim.

FIG. 4 depicts an exemplary user interface 402 of structural analysissoftware platform 210 (shown in FIG. 2) on a display device 222 (alsoshown in FIG. 2) of structural analysis computing device 102. Userinterface 402 may depict a 3D model (also referred to herein as 3Dimage) 404 of room 304. In the exemplary embodiment, 3D model 404 maydisplayed with one or more automatically extracted measurements 406 ofroom 304, such as wall length(s) and/or wall height(s). User interface402 may include additional features, including a menu 410 of rooms ofstructure 302 that may be viewed thereon. In one embodiment, menu 410includes status indicators 412 that indicate whether 3D image(s) areavailable for particular rooms of structure 302. In the illustratedembodiment, status indicators 412 indicate that a kitchen, downstairswater closet, and living room (room 304) may have 3D image(s) available,whereas an upstairs bedroom may not.

Menu 410 may depict a selected room 414, which is room 304 or the livingroom, in the illustrated embodiment. User interface 402 may also includea “Quick Facts” portion 416 or window configured to display facts aboutthe selected room 414 to user 300 (e.g., square footage, ceiling height,etc.).

Additionally, in the exemplary embodiment, user interface 402 mayinclude a policyholder identification field 420 and a claimidentification field 422, such that any information input to, and/orextracted from, structural analysis software platform 210 may be savedfor evaluation of a claim on structure 302. Policyholder identificationfield 420 may be configured to receive a policyholder identifier 424(“XXXXDoe” in the illustrated embodiment), which may include apolicyholder name and/or an alphanumeric identifier associated with thepolicyholder (e.g., an alphanumeric identifier assigned by an insuranceprovider that provides an insurance policy associated with structure302).

Claim identification field 422 may be configured to receive and/ordisplay a claim identifier 426. Claim identifier 426 may be entered byuser 300 and may conform to certain naming conventions and/or may beautomatically generated by structural analysis software platform 210based upon the policyholder identifier 424 and/or any other informationor naming conventions. Additionally or alternatively, user interface 402may include other fields, such as a project identification field, a roomidentification field, and/or a comments field.

In the illustrated embodiment, as described above, displayed 3D model404 may include measurements 406 that were automatically extracted bystructural analysis software platform 210 as implemented on structuralanalysis computing device 102. However, user 300 may view 3D model 404and desire additional measurements be extracted and/or displayed.Continuing the above example, user 300 may wish to have measurements ofbroken windows 310, 312 extracted and displayed. Additionally oralternatively, user 300 may wish to have measurements of damaged portion316 of floor 314 be extracted and displayed.

FIG. 5 depicts one exemplary embodiment of structural analysis softwareplatform 210 (shown in FIG. 2) extracting additional measurements. Morespecifically, structural analysis software platform 210 may receiveinput and instructions from user 300 to extract a width measurement ofbroken window 310 for a claim thereon. User 300 may select (e.g., taps,clicks, etc.) a first input location 502 on 3D image 404 of room 304using input device 224 (shown in FIG. 2, e.g., touch screen, mouse,keyboard, etc.) of structural analysis computing device 102. In theillustrated embodiment, first input location 502 may represent a firstphysical location of a first edge or side 320 of broken window 310.Structural analysis software platform 210 may receive an indication offirst input location 502 from input device 224. User 300 may select asecond input location 504 on 3D image 404 of room 304 using input device224. Second input location 504 may represent a second physical locationof a second edge or side 322 of broken window 310. Structural analysissoftware platform 210 may receive an indication of second input location504 from input device 224.

Structural analysis software platform 210 may calculate a first distance506 between first input location 502 and second input location 504,relative to display device 222 and/or user interface 402. Structuralanalysis software platform 210 may use first distance 506 and extractedmeasurement(s) 306 (and/or additional 3D photogrammetry techniques,algorithms, and/or functionality) to calculate a second distance (notshown) between the first physical location, or first edge 320 of brokenwindow 310, and the second physical location, or second edge 322 ofbroken window 310. Accordingly, the second distance may be displayed on3D image 404 as the requested additional measurement of the width ofbroken window 310.

This “point and click” process may implemented any number of times foruser 300 to request additional measurements from structural analysissoftware platform 210, until all measurements necessary for processingthe claim are extracted. In alternative embodiments, additionalmeasurements may be requested using alternative methods, includinginputting coordinates of first and second input locations 502, 504,using another input syntax to represent first and second input locations502, 504 (e.g., voice commands), and/or any other methods. Alternativelyor additionally, structural analysis software platform 210 mayautomatically extract additional measurements using machine learningfunctionality (e.g., neural networks, decision trees, logic programming,etc.). For example, structural analysis software platform 210 may beconfigured to recognize windows in a structure and may be configured tolearn that measurements of windows (e.g., width and height) arefrequently requested by user 300. Structural analysis software platform210 may then automatically extract window measurements from 3D images404.

As another example, structural analysis software platform 210 may beconfigured to recognize keywords in a claim identifier, such as“window,” “break-in”, “fire”, etc. and may be configured to associateparticular additional measurements that are frequently requested forclaims including those keywords. Structural analysis software platform210 may then automatically extract additional measurements according torecognized keywords.

Additionally, in some embodiments, structural analysis software platform210 may be configured to analyze 3D image 402 to determine additionaldata associated with structure 302. For example, structural analysissoftware platform 210 may determine building materials and/or status ofvarious features of structure 302, such as a flooring material; whethera window is double- or single-paned; whether a feature needs repair,replacement, and/or cleaning; how much of a feature is damaged; etc.

FIG. 6 depicts an exemplary 3D model (also referred to herein as a “3Dimage”) 602 of structure 302 (shown in FIG. 3). 3D model 602 may bedisplayed to user 300 on user interface 402 such that user 300 maynavigate between various rooms 604 of structure 302 to view 3D imagesthereof. For example, if user 300 is generating and/or submitting aclaim involving more than one room, user 300 may select rooms 604 ofinterest on 3D model 602 to navigate therebetween (i.e., switch viewstherebetween). Structural analysis software platform 210 may beconfigured to generate 3D model 602 based upon a plurality of 3D imagescaptured of rooms 604 therein.

Structural analysis software platform 210 may be configured to saveand/or export a data file including any extracted, received, and/orcalculated information, such as 3D models 402 and/or 602, extractedmeasurements 406, additional measurements, policyholder identifier 424,claim identifier 426, and/or any other information. In one exemplaryembodiment, structural analysis software platform 210 may be configuredto export the data file to claims evaluation software platform 212(shown in FIG. 2) to evaluate the information therein and determine aclaim disbursement amount associated therewith.

FIGS. 7 and 8 illustrate a second exemplary use of mobile photogrammetrysystem 100 (shown in FIG. 1). More specifically, FIGS. 7 and 8illustrate using mobile photogrammetry system 100 for object inventory,for example, in a “before-and-after” break-in scenario. FIG. 7 depicts afirst 3D image 700 (e.g., a “before” 3D image 700) of a room 702. Room702 may have various contents 704 therein that may be of particularmonetary and/or sentimental value to a user (e.g., user 300 as shown inFIG. 3, not shown in FIGS. 7 and 8). In the illustrated embodiment,contents 704 include a painting 706, a sculpture 708, and a cabinet 710.Accordingly, user 300 may capture first 3D image 700 using a structuralanalysis computing device (e.g., structural analysis computing device102 as shown in FIGS. 1-4, not shown in FIGS. 7 and 8) to show alocation of contents 704 and to create an inventory of contents 704.User 300 may use first 3D image 700 to purchase an insurance policy oncontents 704 with an insurance provider.

FIG. 8 depicts a second 3D image 800 (e.g., an “after” image 800) ofroom 702 after, for example, a break-in and theft. Second 3D image 800depicts contents 704 and shows that painting 706 and sculpture 708 aremissing and that cabinet 710 has been damaged (e.g., is missing a door).User 300 may capture second 3D image 800 using structural analysiscomputing device 102 to show a state of room 702 after the theft inorder to identify what is missing and/or damaged to the insuranceprovider in a claim.

User 300 may use structural analysis computing device 102 to submitcaptured first and second 3D images 700 and 800 to structural analysissoftware platform 210 (shown in FIG. 2). Structural analysis softwareplatform 210 may be configured to automatically extract measurements 802from first and/or second 3D images 700 and 800. In some embodiments,structural analysis software platform 210 may use extracted measurements802 to identify differences 804 between first and second 3D images 700and 800. Additionally or alternatively, structural analysis softwareplatform 210 may be configured to use other 3D image analysis toautomatically identify differences 804 between first and second 3Dimages 700 and 800, such as color comparison. Structural analysissoftware platform 210 may be configured to save and/or export identifieddifferences 804, first and/or second 3D image(s) 700 and/or 800, and/orany other extracted, received, and/or calculated information in a datafile, for example, for use by claims evaluation software platform 212(shown in FIG. 2).

FIG. 9 illustrates a third exemplary use of mobile photogrammetry system100 (shown in FIG. 1). More specifically, FIG. 9 depicts an exemplary 3Dimage 900 of a damaged feature 902 of a person (not specifically shown)for analysis using mobile photogrammetry system 100. A user (e.g., user300 as shown in FIG. 3) may capture 3D image 900 using a structuralanalysis computing device (e.g., structural analysis computing device102 as shown in FIGS. 1-4). 3D image 900 may include one or more viewsof damaged feature 902, in this example a dog bite 904 on a forearm 906.

User 300 may submit capture 3D image 900 to structural analysis softwareplatform 210 (shown in FIG. 2). Structural analysis software platform210 may be configured to automatically extract measurements 910, 912 ofdamaged feature 902. Structural analysis software platform 210 may befurther configured to receive instructions from user 300 to extractadditional measurements of damaged feature 902, as described above(e.g., a depth of dog bite 904, measurement(s) of individual teeth marksor bruising therearound, etc.). Structural analysis software platform210 may be configured to save and/or export extracted measurements 910,912, 3D image 700, and/or any other extracted, received, and/orcalculated information in a data file, for example, for use by claimsevaluation software platform 212 (shown in FIG. 2).

FIG. 10 illustrates an exemplary data file 1000 used in mobilephotogrammetry system 100 (shown in FIG. 1). Data file 1000 may have anXML format and/or any other suitable file format for storage and/orexport between various applications or software platforms (e.g.,structural analysis software platform 210 and/or claim evaluationsoftware platform 212, shown in FIG. 2). Data file 1000 may be saved ina memory device, such as memory device 108 (shown in FIG. 1) and/ormemory 220 (shown in FIG. 2). Data file 1000 may include additional,fewer, and/or different fields than as shown in the illustratedembodiment. For example, data file 1000 may include one or more 3Dimage(s).

In the exemplary embodiment, at least some of data file 1000 may begenerated, received, saved, and/or exported by structural analysissoftware platform 210. For example, the claim identifier (e.g., claimidentifier 426, shown in FIG. 4), an object identifier such as a roomname, feature, room type, ceiling type, window type, window subtype,measurement(s), material, and/or status may be exported by structuralanalysis software platform 210 as data file 1000.

At least some of data file 1000 may be generated, saved, and/or exportedby claim evaluation software platform 212. For example, claim evaluationsoftware platform 212 may receive at least some of data file 1000 fromstructural analysis software platform 210 and/or may retrieve the atleast some of data file 1000 memory 108. Claim evaluation softwareplatform 212 may be configured to analyze the data contained therein asit corresponds to an insurance claim associated therewith, as identifiedby the claim identifier. Claim evaluation software platform 212 may beconfigured to determine whether data file 1000 (as received) isassociated with an existing project and/or claim (e.g., using the claimidentifier and/or other data, such as a project identifier orpolicyholder identifier).

If data file 1000 (as received) is not associated with an existingproject and/or claim, claim evaluation software platform 212 may beconfigured to generate a new project and/or claim and import data fromdata file 1000 into the new project and/or claim. If data file 1000 (asreceived) is associated with an existing project and/or claim, claimevaluation software platform 212 may be configured to import data fromdata file 1000 that is not present in the existing project and/or claim,and/or that is different from existing data in the project and/or claim.

Claim evaluation software platform 212 may be further configured toevaluate the project and/or claim based upon data file 1000 and mayappend data file 1000 to include the results of that evaluation. Forexample, in the illustrated embodiment, claim evaluation softwareplatform 212 may be configured to determine one or more of material,status, and/or estimate(s), based upon data file 1000 (as received),including any 3D images therein.

In one exemplary embodiment, claim evaluation software platform 212 maybe configured to identify one or more feature(s) of an object, which mayinclude characteristics and/or components of the object. For example,individual rooms may be features of a home, and a type or manufacturerof a personal article may be a feature of that personal article. In someembodiments, as described herein, claim evaluation software platform 212is configured to identify, assess, and/or quantify damage to an insuredobject as part of an insurance claims handling process. Accordingly, insuch embodiments, claim evaluation software platform 212 may identify anature of damage to an object (e.g., fire, smoke, water, hail, wind,theft), an extent of the damage done to the object (e.g., whether repairor replacement is needed, what kind of repair is needed, etc.), and/or aparticular feature that is damaged (e.g., a window of a home or a sidemirror of a vehicle). Claim evaluation software platform 212 may employa number of image-processing techniques to analyze the 3D images, suchas object recognition, optical character recognition, machine learning,and/or any other kind of image processing. After such identification,claim evaluation software platform 212 may estimate a repair/replacementcost for the damaged object.

Claim evaluation software platform 212 may retrieve reference and/orhistorical information from memory device 108 in order to evaluate datafile 1000. For example, claim evaluation software platform 212 may useimages, values, past claims, indices, keywords, and/or any other storedinformation to determine a material of an feature, a status of afeature, a determined action to be taken (e.g., cleaning vs. repair),and/or an estimate for that determined action (e.g., the estimatedrepair/replacement cost). In some embodiments, claim evaluation softwareplatform 212 may further employ machine learning functionality to makeany of the above determinations.

In one particular embodiment, claim evaluation software platform 212 isconfigured to retrieve “pre-damage” images of a damaged object for whicha claim is being submitted. Similar to the situation described abovewith respect to FIGS. 7 and 8, a user or owner of the object may submitone or more pre-damage 3D images, for example, when requesting a quotefor a policy associated with the object. Pre-damage 3D image(s) may beprocessed at the time they are received (e.g., by claim evaluationsoftware platform 212, structural analysis software platform 210, and/oranother software platform implemented by insurance server 112, shown inFIG. 1). After damage to the object has occurred in an “insurance event”or “damage event”, the owner of the insurance policy (and/or any otherperson) may capture the post-damage 3D images of the object usingstructural analysis computing device 102, as described herein. Claimevaluation software platform 212 may be configured to retrieve thepre-damage 3D image(s) and compare pre- and post-damage 3D images inorder to identify features of the object that have been damaged (e.g.,rooms of a home, objects within a room, components of a vehicle, etc.).In one embodiment, claim evaluation software platform 212 analyzes thepre-damage 3D image(s) to identify features of the insured object, suchas a type of the object and/or a manufacturer of the object as well ascomponents (e.g., parts) of the object. Claim evaluation softwareplatform 212 may be configured to estimate a repair or replacement costfor the undamaged object and/or establish a baseline status for theundamaged object. The baseline status may account for any damage to theobject that has occurred before the “insurance event” (e.g., dents on avehicle). Claims evaluation software platform 212 may then analyze thepost-damage 3D image(s) to identify features thereof, and may comparethe features of the pre- and post-damage 3D images to estimate arepair/replacement cost for any damaged features.

Claim evaluation software platform 212 may be configured to generate anestimate for any repairs, replacements, cleaning, abatement, etc.identified in data file 1000. In other words, claim evaluation softwareplatform 212 may generate a claim disbursement amount 1002. In theillustrated embodiment, claim disbursement amount 1002 may be a total ofthe estimates in data file 1000 (e.g., $200+$900+$300=$1,400). It shouldbe understood that where there are multiple objects or features forwhich a claim has been submitted, claim evaluation software platform 212may be configured to compile claim disbursement amounts for individualdamaged object/feature. In particular, in some embodiments, claimevaluation software platform 212 may generate an inventory list of eachdamaged object/feature. Claim evaluation software platform 212 mayestimate a repair/replacement cost for each item on the inventory list,and then may total each individual cost to determine a total claimdisbursement amount for the entire inventory list. The estimate for anyparticular repair/replacement may be generated according to the featuresof the object, the nature of the damage, and/or the extent of thedamage. For example, a damaged component of an object from onemanufacturer may cost most to repair/replace than a damaged component ofanother from a different manufacturer. Claim evaluation softwareplatform 212 may append and/or edit data file 1000 to include anydetermined values and/or fields associated therewith.

Moreover, claim evaluation software platform 212 may be configured toleverage attributes of a particular insurance policy when estimatedclaim disbursement amounts. For example, a particular policy may coverwind damage but not hail damage. In such an example, where claimevaluation software platform 212 determines that a feature has beendamaged by wind, claim evaluation software platform 212 may estimate arepair/replacement cost as part of a claim disbursement amount but maynot treat determined hail damage in the same manner.

Additionally or alternatively, at least some of data file 1000 may beinput by a user (e.g., user 300, shown in FIG. 3). For example, user 300may make certain determinations, such as whether a feature should becleaned or repaired, and/or the nature of damage to an object, where thenature of the damage is unclear. The user may enter such determinationsinto corresponding fields to be included in data file 1000.

In some embodiments, structural analysis computing device 102 (shown inFIGS. 1-4) may be configured to transmit data file 1000 to anothercomputing device, such as insurance server 112 (shown in FIG. 1) and/ormemory device 108. For example, structural analysis computing device 102may transmit data file 1000 including claim disbursement amount 1002 toinsurance server 112 for disbursement of the corresponding amount to apolicyholder. As another example, structural analysis computing device102 may transmit data file 1000 without a claim disbursement amount toinsurance server 112, and insurance server 112 may use data file 1000 todetermine a claim disbursement amount. In some embodiments, insuranceserver 112 may be configured to implement claim evaluation platform 212to retrieve data file 1000 and/or determine a claim disbursement amount.

Additionally or alternatively, in some embodiments, structural analysiscomputing device 102 may transmit data file 1000 including claimsdisbursement amount 1002 in a claim generation or claim submissionsignal to insurance server 112. The claim generation signal may beconfigured to activate insurance server 112 and to cause insuranceserver 112 to automatically generate and/or populate a claims form withinformation from data file 1000. Additionally or alternatively, claimevaluation software platform 212 may generate and/or populate a claimsform and facilitate display of the claims form for review by a user ofstructural analysis computing device 102. Claim evaluation softwareplatform 212 may include the estimate claim disbursement amount in thepre-populate claim form, such that the user may accept the claimdisbursement amount or may request modifications thereto.

Exemplary Server Computing Device

FIG. 11 depicts an exemplary configuration of a server computing device1102. Server computing device 1102 may be representative of databaseserver 106, and/or insurance server 112 (both shown in FIG. 1). Servercomputing device 1102 may include a processor 1105 for executinginstructions. Instructions may be stored in a memory area 1110, forexample. Processor 1105 may include one or more processing units (e.g.,in a multi-core configuration).

Processor 1105 may be operatively coupled to a communication interface1115 such that server computing device 1102 may be capable ofcommunicating with a remote device, such as structural analysiscomputing device 102 or another server computing device 1102. Forexample, communication interface 1115 may receive requests fromstructural analysis computing device 102 via the Internet.

Processor 1105 may also be operatively coupled to a storage device 1120.Storage device 1120 may be any computer-operated hardware suitable forstoring and/or retrieving data. In some embodiments, storage device 1120may be integrated in server computing device 1102. For example, servercomputing device 1102 may include one or more hard disk drives asstorage device 1120. In other embodiments, storage device 1120 may beexternal to server computing device 1102 and may be accessed by aplurality of server computing devices 1102. For example, storage device1120 may include multiple storage units, such as hard disks or solidstate disks in a redundant array of inexpensive disks (RAID)configuration. Storage device 1120 may include a storage area network(SAN) and/or a network attached storage (NAS) system.

In some embodiments, processor 1105 may be operatively coupled tostorage device 1120 via a storage interface 1125. Storage interface 1125may be any component capable of providing processor 1105 with access tostorage device 1120. Storage interface 1125 may include, for example, anAdvanced Technology Attachment (ATA) adapter, a Serial ATA (SATA)adapter, a Small Computer System Interface (SCSI) adapter, a RAIDcontroller, a SAN adapter, a network adapter, and/or any componentproviding processor 1105 with access to storage device 1120.

Memories 108 (shown in FIG. 1), 220 (shown in FIG. 2), and/or 1110 mayinclude, but are not limited to, random access memory (RAM) such asdynamic RAM (DRAM) or static RAM (SRAM), read-only memory (ROM),erasable programmable read-only memory (EPROM), electrically erasableprogrammable read-only memory (EEPROM), and non-volatile RAM (NVRAM).The above memory types are example only, and are thus not limiting as tothe types of memory usable for storage of a computer program.

Exemplary Computer-Implemented Method of Extracting StructuralCharacteristics from 3D Images

FIG. 12 illustrates a flowchart of an exemplary computer-implementedmethod 1200 for extracting structural characteristics of a structureusing mobile photogrammetry system 100 (shown in FIG. 1). Moreparticularly, at least some steps of method 1200 may be implementedusing structural analysis computing device 102 (also shown in FIG. 1),for example, using at least one of structural analysis software platform210 and claim evaluation platform 212 (both shown in FIG. 2). Method1200 may include accessing 1202 a 3D image (e.g., 3D image 404, shown inFIG. 4) including an object (e.g., structure 302 and/or room 304, shownin FIG. 3). As described herein, the 3D image may be captured using anobject sensor (e.g., object sensor 110, shown in FIGS. 1 and 2) includedin structural analysis computing device 102.

Method 1200 may further include automatically extracting 1204 a firstplurality of measurements of the object from the 3D image, anddisplaying 1206 the 3D image on a user interface (e.g., user interface402) with the first plurality of measurements of the object pictured inthe 3D image. Method 1200 may also include generating 1208 a data file(e.g., data file 1000, shown in FIG. 10) including the 3D image and thefirst plurality of measurements, and storing 1210 the data file within amemory (e.g., memory device 108, shown in FIG. 1). Method 1200 mayinclude additional, less, or alternate actions, including thosediscussed elsewhere herein.

Exemplary Structural Analysis Computing Device

FIG. 13 depicts a diagram 1300 of components of one or more exemplarystructural analysis computing devices 1310 that may be used in mobilephotogrammetry system 100 (shown in FIG. 1). Structural analysiscomputing device 1310 may be similar to structural analysis computingdevice 102 and/or structural analysis computing device 104 (both shownin FIG. 1). FIG. 12 further shows a configuration of data in database1320, which may be similar to memory device 108 (also shown in FIG. 1).Database 1320 may include, for example, 3D images 1322, data files 1324,reference information 1326, projects 1328 (e.g., project, object, and/orclaim identifiers) and other data as described elsewhere herein.Database 1320 may be in communication with several separate componentswithin structural analysis computing device 1310, which perform specifictasks.

More specifically, structural analysis computing device 1310 may includean object sensor 1330 configured to capture 3D images 1322 of an objectand to make 3D images accessible to other components of structuralanalysis computing device 1310. Structural analysis computing device1310 may also include an extracting component 1340 configured toautomatically determine or extract a first plurality of measurements ofthe object from 3D image 1322. Structural analysis computing device 1310may further include a displaying component 1350 (e.g., display device222, shown in FIG. 2) configured to display 3D image 1322 on a userinterface (e.g., user interface 402, shown in FIG. 4) with the firstplurality of measurements of the object pictured in 3D image 1322.Structural analysis computing device 1310 may additionally include agenerating component 1360 configured to generate a data file 1324including 3D image 1322 and the first plurality of measurements.

Exemplary Insurance-Related Functionality: Mobile Photogrammetry Systemand Quote Generation

FIG. 14 depicts a schematic view of a first alternative embodiment of amobile photogrammetry computer system 1400. Mobile photogrammetry system1400 may be similar in many aspects to mobile photogrammetry system 100(shown in FIG. 1). Where the same or functionally similar elements inFIG. 14 are described with respect to FIG. 1, the same referencenumerals are employed. In mobile photogrammetry system 1400, inparticular, insurance server 112 may include a quote generation platform1412. Quote generation platform 1412 may be implemented on a processor(e.g., processor 1105, shown in FIG. 11) of insurance server 112. Itshould be understood that the functionality described herein withrespect to quote generation platform 1412 may be performed byalternative software platforms implemented on insurance server 112and/or structural analysis computing device(s) 102, 104.

Quote generation platform 1412 may be configured to usethree-dimensional (3D) images 1424 captured using structural analysiscomputing device(s) 102, 104 to generate an insurance quote for a user(e.g., user 300, shown in FIG. 3) thereof. The generated insurance quotemay be associated with any insurable asset, including a structure (e.g.,a home or business), an object (e.g., antiques, art, furniture, etc.), avehicle, and/or any other insurable asset. In particular, user 300 mayuse structural analysis computing device 102 to capture at least one 3Dimage 1424 of the insurable asset. User 300 may capture a plurality of3D images 1424 of the insurable asset, for example, to capture multipleangles or particular features of the insurable asset. User 300 then mayuse structural analysis computing device 102 to transmit a quote requestsignal 1420 to insurance server 112, quote request signal 1420 includinga quote request 1422 requesting an insurance quote for the insurableasset pictures in the 3D image(s) 1424. The communications ortransmissions between the structural analysis computing device 102 andinsurance server 112 may be via wireless communication or datatransmission over one or more radio frequency links. For instance,insurance server 112 may be configured to receive and/or transmit dataover a wireless communication channel to a wireless mobile deviceassociated with a user 300.

In certain embodiment, insurance server 112 may be configured tomaintain and provide a graphical user interface (UI) for user 300 toaccess the quote generation functionality of insurance server 112. Forexample, insurance server 112 may provide a quote request application(“app”) 1410 for user 300 to access to request a quote. Quote requestapp 1410 may be downloaded, installed, and run using structural analysiscomputing device 102 (and/or any other user computing device, notshown). Quote request app 1410 may prompt user 300 to attach 3D image(s)1424 to quote request 1422 for the insurable asset. For example, user300 may upload 3D image(s) 1424 captured using structural analysiscomputing device 102 to quote request app 1410. Quote request app 1410may further prompt user 300 for additional information associated withthe insurable asset, user 300, and/or the requested quote. For example,quote request app 1410 may prompt user 300 to enter security information(e.g., various safety features of user 300's home or building at whichthe insurable asset is stored, such as fire hazards or fire safetyfeatures, theft risks, etc.), use information (e.g., how often aparticular vehicle is used, how it is used, who uses it), accessinformation (e.g., who other than user 300 has access to the insurableasset), worth or value information (e.g., an estimated or appraisedvalue of the insurable asset), and/or any other information.Additionally or alternatively, quote request app 1410 may prompt user300 to enter personal and/or insurance information for the quoterequest, such as policy credentials for user 300 (e.g., if user 300already has one or more insurance policies maintained by insuranceserver 112). It should be understood that quote request app 1410 mayprompt user 300 to enter any kind of information, such as user names,user ages, addresses, cities of residence, zip codes, etc. The questionsmay relate to identifying both user 300 and the insurable asset.

Structural analysis computing device 102 (and/or the user computingdevice through which user 300 accesses insurance server 112 using quoterequest app 1410) may prepare quote request 1422. Preparing quoterequest 1422 may include preparing 3D image(s) 1424 for transmittal aswell as including all user-entered information, as described above.Structural analysis computing device 102 may transmit quote requestsignal 1420 to insurance server 112 for processing using quotegeneration platform 1412.

Quote generation platform 1412 may process quote request 1422 todetermine a quote value associated with the insurable asset. Suchprocessing may include several steps. For example, in certainembodiments, quote generation platform 1412 may be configured to process3D image(s) 1424 to identify the insurable asset pictured therein. Inone embodiment, 3D data or 3D images of known insurable assets may beinput into a machine learning program (such as pattern recognition,object recognition, optical character recognition, deep learning, neuralnetwork, or combined learning program) to train the machine learningprogram to identify insurable assets from a new 3D data or 3D image setreceived from a user's mobile device.

In some embodiments, such identification may be included in quoterequest 1422 (e.g., may be provided by user 300 during preparation ofquote request 1422 in the app). Quote generation platform 1412 may befurther configured to process 3D image(s) 1424 to identify a status ofthe insurable asset pictured therein. For example, the status mayindicate a value of the insurable asset, as well as supplemental detailssuch as a pre-insured level of wear of the insurable asset, includingany pictured damages or flaws which may affect a value of the insurableasset. In other words, quote generation platform 1412 may use received3D images 1424 to establish a baseline value or pre-insured status ofthe insurable asset. This baseline value or associated pre-insuredstatus may be used at a future time to determine claim disbursementamounts according to the damage incurred versus the baseline value orassociated pre-insured status (e.g., in a situation similar to thatdepicted in FIGS. 7 and 8). In one embodiment, 3D data or 3D images ofknown insurable assets having known statuses may be input into a machinelearning program (such as pattern recognition, object recognition,optical character recognition, deep learning, neural network, orcombined learning program) to train the machine learning program toidentify the insurable assets, as well as the current status of eachinsurable asset identified, from a new 3D data or 3D image set receivedfrom a user's mobile device.

In some embodiments, quote generation platform 1412 may include theabove-described functionality of structural analysis platform 210 and/orclaim analysis platform 212 (both shown in FIG. 2) to analyze andprocess 3D image(s) 1424. In other embodiments, structural analysiscomputing device 102 may be configured to perform this statusidentification prior to transmitting the quote request. For example,structural analysis computing device 102 may employ structural analysisplatform 210 to process and analyze 3D image(s) 1422 as describedelsewhere herein. Accordingly, quote generation platform 1412 mayreceive output from structural analysis platform 210 and process saidoutput during the quote generation process.

In one embodiment, 3D data or 3D images of known insurable assets havingknown statuses, and appropriate or associated insurance quotes may beinput into a machine learning program (such as pattern recognition,object recognition, optical character recognition, deep learning, neuralnetwork, or combined learning program) to train the machine learningprogram to identify the insurable assets, as well as the current statusof each insurable asset identified and an appropriate insurance quotecovering the insurable assets, from a new 3D data or 3D image setreceived from a user's mobile device.

Quote generation platform 1412 may also access memory database 108(and/or any other supplementary data sources, not shown) for informationduring a quote generation process. Memory database 108 may includepublic records, open content or open source databases (e.g., thosecontaining “tagged” photographs of geographic locations), or databasesoperated by third party companies, for example. The machine learningprogram may also be trained to identify a value for each insurance assetthat is include within the 3D data or 3D image data, such as the quotevalues discussed below.

In one embodiment, quote generation platform 1412 may generate one ormore quotes 1432, each quote including a respective quote valueassociated with the insurable asset. The quote value may include adetermined value of the insurable asset. The quote value may alsoinclude but also a number of details associated with an insurance policyfor the insurance asset, such as a premium rate, any applicablediscounts, a payment schedule, any applicable deductibles, a replacementor repair cost associated with the insurable asset, and/or any claimdisbursement information (e.g., a minimum or maximum claim disbursementamount associated with particular types of potential damage to theinsurable asset). Quote generation platform 1412 may then transmit theone or more generated quote(s) 1432 in a quote response signal 1430 tostructural analysis computing device 102 (and/or any other usercomputing device through which user 300 accesses insurance server 112using quote request app 1410), such as via wireless communication ordata transmission over one or more radio frequency links and/or wirelesscommunication channel(s). In particular, quote generation platform 1412may transmit quote response signal 1430 to structural analysis computingdevice 102 with instructions for structural analysis computing device102 to activate and display the generated quote(s) 1432 in quote requestapp 1410 to user 300. In one embodiment, insurance server 112 mayprovide an insurance quote app (or claim app) to a customer's mobiledevice or structural analysis computing device 102, or otherwise provideaccess to an app 1410 for installation or download to the customer'smobile device or structural analysis computing device 102.

User 300 may use quote request app 1410 to view and compare (whereapplicable) the one or more generated quote(s) 1432. User 300 mayfurther use quote request app 1410 to select a quote 1432 associatedwith the insurable asset that user 300 wishes to purchase or initiate.In some embodiments, user 300 may select an option to request changes toa selected quote 1432. Such changes may be accepted or declinedautomatically, according to particular rules. Alternatively, such arequest may initiate contact between an underwriter and user 300 inorder to “manually” accept or decline user 300's requested changes.

Exemplary Machine Learning

As discussed above, a processor or a processing element may be trainedusing supervised or unsupervised machine learning, and the machinelearning program may employ a neural network, which may be aconvolutional neural network, a deep learning neural network, or acombined learning module or program that learns in two or more fields orareas of interest. Machine learning may involve identifying andrecognizing patterns in existing data (such as 3D data or 3D image data)in order to facilitate making predictions for subsequent data (again,such as 3D data or 3D image data). Models may be created based uponexample inputs of data in order to make valid and reliable predictionsfor novel inputs.

Additionally or alternatively, the machine learning programs may betrained by inputting sample data sets or certain data into the programs,such as 3D image data, insurance-related data, financial or value data,and other data discuss herein. The machine learning programs may utilizedeep learning algorithms are primarily focused on pattern recognition,and may be trained after processing multiple examples. The machinelearning programs may include Bayesian program learning (BPL), voicerecognition and synthesis, image or object recognition, opticalcharacter recognition, and/or natural language processing—eitherindividually or in combination. The machine learning programs may alsoinclude natural language processing, semantic analysis, automaticreasoning, and/or machine learning.

In supervised machine learning, a processing element may be providedwith example inputs and their associated outputs, and may seek todiscover a general rule that maps inputs to outputs, so that whensubsequent novel inputs are provided the processing element may, basedupon the discovered rule, accurately predict the correct output. Inunsupervised machine learning, the processing element may be required tofind its own structure in unlabeled example inputs.

In one embodiment, machine learning techniques may be used to extractthe relevant insurable asset information from 3d images and/or otherdata. The machine learning programs may be trained with 3D data toidentify insurable assets or objects; identify their status; estimate avalue or replacement cost for the insurable assets; generate insurancequotes for the insurable assets identified; identify damage (or theextent of damage) to insurable assets after an insurance-related event(e.g., fire, flood, hurricane, tornado); generate proposed insuranceclaims for insureds after an insurance-related event; and identify orestimate other items or values, including those discussed elsewhereherein.

Exemplary Functionality

The present embodiments relate to 3D scanning, which may also bereferred to 3D light scanning, 3D laser scanning, and/orstructured-light 3D scanning. The 3D scanners discussed herein may alsoinclude any device that measures the physical world using lasers,lights, or x-rays, and generates dense point clouds or polygon meshes.The 3D scanners may also include 3D digitizers, lasers scanners, whitelight scanners, CT, LIDAR, etc. and other devices that capture thegeometry of physical objects (such as rooms, homes, vehicles, personalbelongings, people, pets, etc.) with numerous measurements. Forinstance, the devices may emit light beams out which are reflected offof objects, and the devices may then capture the bounce back of thelight beams emitted.

In a preferred embodiment, a 3D scanner for obtaining interiorstructural room measurements may include a structure sensor fromOccipital, Inc. that is configured with a tablet, such as an iPad Air 2.Alternatively, a Google Project Tango 3D sensing-enabled smart phone ortablet may be used. Numerous other 3D scanners may be utilized,including those with integrated depth sensing.

The present embodiments provide a mobile 3D sensing smart deviceapplication that will automate and complete photo-documentation,measurement and room data entry steps associated with insuranceunderwriting, quoting, or claim handling, such as with homeowner's orrenters insurance. A software feature or application may create avirtual room or virtual home, with accurate dimensional information.Room measurements may be estimated that include wall lengths, wallheights, missing wall dimensions, door and window opening dimensions,cabinetry lengths, countertop dimensions, fireplace dimensions, etc. Alllengths may be embedded within, associated with, or highlighted upon, avirtual depiction of a room or home.

The software application may upload or download digital images of damageto rooms or the home taken by, and/or transmitted by, an insured'smobile 3D sensing smart device. The photos may be uploaded to aninsurance claim system. An extent of damage to the interior (and/orexterior) of a room and/or a home (or other structure) may be estimated,as well as a replacement or repair cost may be estimated based uponcomputer analysis of the images acquired.

The software application may analyze pre-insurance event and/orpost-insurance event 3D data and/or 3D digital image data. For instance,from 3D data acquired from the 3D scanner, the software application may(i) determine room types; (ii) name the rooms according to type of room;(iii) determine room sizes; (iv) determine types of ceilings, windows,flooring, doors, and/or doorways; and/or (v) determine staircasemeasurements to facilitate repairing interior damage after an insurancerelated-event (such as an event leading to fire, smoke, or water damageto all or part of a home).

In one embodiment, a computer-implemented method using 3D data toestimate damage and/or estimate repairs may be provided. The method mayinclude (1) determining that a room within a structure requiresphotographic documentation, scope measurement dimensions, and/or anestimate for damage repairs. The method may include (2) accessing mobile3D Photogrammetry, such as an insurance claim handler or insuredaccessing a 3D scanning application on his or her mobile device.

The method may also include (3) inputting or retrieving a claim numberor insurance policy number, an insured's named, and/or a room nameselected from a drop down menu (such as alcove, aisle, attic, ballroom,basement, bedroom, bonus room, breezeway, closet, den, dining room,entryway, exercise room, furnace room, garage, great room, hall, homecinema, kitchen, laundry room, living room, lobby, loft, nursery,office, pantry, recreation room, studio, sunroom, utility room, winecellar, or workshop). The method may include inputting or determining aroom type (e.g., box, L-shape, T-shape, or U-Shape), a ceiling type(e.g., float sloped, peaked, or tray), window type (e.g., bay, box, bow,picture, hung, casement), window subtype (e.g., circle, flat arch,octagon, round, round arch, trapezoid, triangle), doorway type (e.g.,standard, bifold, sliding, dutch, pocket, overhead, gate), doorwaysubtype (e.g., flush, French, half louvered, paneled), and/or staircasetype (e.g., regular, regular with landing, L-shaped, etc.). In someembodiments, the foregoing information may be entered by a user takingthe 3D scans. In other embodiments, the foregoing information may bedetermined from analysis of the 3D data acquired and/or 2D digital imagedata of the room/home.

The method may also include (4) scanning the room using the mobile 3DPhotogrammetry application running on a 3D sensing smart phone or tablet(e.g., an iPad with an Occipital Structure Sensor or Project Tango 3Dsensor-enabled smart phone or tablet). After which, the method mayinclude (5) the mobile 3D Photogrammetry application or an Estimationapplication providing a 3D rendering of the room. The application mayprovide a 3D image of the room with all wall dimensions depicted.

The method may further include (6) reviewing the 3D image of the room.For instance, an insured or claim handler may review the 3D room imageand determine what other required room measurements are required. Forinstance, as shown in FIGS. 4 and 5, a user may view a 3D room renderingincluding all wall measurements on a smart phone or other mobile device.A floorplan view of rooms may also be generated and displayed.

The method may further include (7) completing any additional roommeasurements. For instance, an insured or insurance providerrepresentative may navigate within the 3D room image and “point andclick” on required measurement items not automatically self-populatedbased upon pre-designated app requirements (e.g., lineal footage of thebase cabinetry in a kitchen). The “point and click” functionality may beprovided to complete any additional measurements and/or annotationswithin the 3D image required.

The method may also include (8) the insured or insurance providerrepresentative (such as an insurance agent or claim handler) clickingupon a “Complete and Export” icon. For instance, once the 3D room imageprovides all the room data desired, the user may click a “complete andexport” icon on the application user interface.

The method may also include (9) employing a 3D Photogrammetry or anEstimation Application that creates an XML data file. For instance, theapplication may take room data and room measurements supplied in the 3Dimage of the room and creates a XML data file that may be consumed by aninsurance provider remote server and/or estimating platform software.The room data and room measurements may be initially input by the useracquiring the 3D data, or may instead be determined from computeranalysis of (i) the 3D data acquired and/or (ii) other digital imagedata acquired by a mobile device (e.g., smart phone or tablet).

The method may further include (10) exporting claim and/or room data toan insurance provider estimation platform software. For example, the 3Dimage of the room and room data supplied in the XML data file may beexported to an estimatics platform software. After which, the method mayinclude (11) the estimatics software system generating a new project oradditional room on a pre-existing project with the room data.

Upon receipt of data, the estimatics software may first review the claimnumber and policyholder name. If no such project yet exists with thatclaim identification data, the estimatics software automaticallysystem-generates the creation of a new project. Upon creation of a newproject, the estimatics software reviews, validates and autopopulates(where possible) the room data provided in the XML data file. On theother hand, if a project exists but is for room data not yet part of theproject, the estimatics software reviews, validates and auto-populates(where possible) the new room data provided in the XML data file.

The method may include storing all estimates and projects (including 3Dimages and measurement annotations) on a remote server or in the Cloud.For instance, upon system-generation of the “new project” or “additionalroom” on a pre-existing project, the estimatics software will send thisdata (3D imagery with measurements and annotations and corresponding XMLdata files) to an estimatics vendor “Cloud” service for storage andfuture usage/reference.

As a result of the above, the solution will generate a virtualillustration of the room; secure the needed measurements; record andsave the required measurements of the room on the virtual depiction ofthe room; create a new project or update an additional room within thatvirtual project; receive inputted or selected room data (room name ortype, ceiling or window type, door or doorway type, staircase type, andmeasurements) or determine such room data and measurements from the 3Dscanner data acquired.

Moreover, the present embodiments may provide exceptional roomphoto-documentation. Unlike 2D images, these 3D images may allow theuser (e.g., insured or insurance provider representative) to navigatewill allow the claim handler to navigate within the image and confirmroom construction elements (flooring material/wall texture/type oflighting/etc.).

The mobile smart device 3D Photogrammetry application may (i)prompt/accept initial claim identification information; (ii)prompt/accept room data (room name/room type/ceiling type/windowtype/window subtype/doorway type/doorway subtype/staircase); (iii) scanand display the interior structure of a room as a 3D image that may benavigated within; (iv) auto-populate all of the room's interiorstructural wall measurements in the 3D image (including: wall lengths,wall heights, missing wall lengths, and/or missing wall heights); (v)provide “point and click” ability to measure the following: cabinetrylengths; cabinetry heights; countertop dimensions; door openingdimensions; window opening dimensions; and/or built-in appliancedimensions; (vi) provide ability to record/save measurements and otherannotations (such as room comments) within the 3D room image; (vii)provide ability to create an XML data file from the room data providedby the user and from within the 3D room image; and/or (viii) provideability to export 3D room image(s) and XML data file(s) to an insuranceprovider estimatics platform software.

The estimatics software may be coded to accept 3D image(s) and theircorresponding XML data file(s). Upon receipt of data, the estimaticssoftware may first review the claim identification data and, if no suchproject yet exists with that claim identification data, the estimaticssoftware may automatically system-generate the creation of a newproject. Upon creation of a new project, the estimatics software mayreview, validate and autopopulate the room data provided in the XML datafile. If a project exists but is for room data not yet part of theproject, the estimatics software reviews, may validate and auto-populatethe new room data provided in the XML data file. The estimatics softwaremay send to the estimatics data to the “Cloud” for storage, and/or maybe coded to allow users Cloud access for project retrieval andsubsequent review of project's room 3D imagery (including measurements).

Exemplary Computer-Implemented Methods Using 3D Data

FIG. 15 depicts an exemplary computer-implemented method 1500 ofestimating repair and/or replacement costs for insured assets using 3Ddata. The method 1500 may include receiving 1502 pre-insurance event 3Ddata of one or more insured assets at a remote server, the 3D data beinggenerated and transmitted by a mobile device of customer/insuredequipped with 3D scanning functionality. The insured assets may includea home, vehicle, boat, and/or personal articles (including antiques,paintings, furniture, electronics, etc.).

The method 1500 may include analyzing 1504 the 3D data (at the remoteserver) to establish baseline or initial condition of the insuredasset(s). The remote server may also analyze 1506 the 3D data toidentify features of the insured assets (such as by inputting the 3Ddata into a machine learning program). The method 1500 may includeestablishing or determining 1508, via the remote server, a replacementcost or value of the insured assets. The method 1500 may includegenerating 1510 an insurance quote for home, auto, personal articles, orother insurance covering the insured asset, and transmitting theinsurance quote to the customer's mobile device for their review.

The method 1500 may include receiving 1512 post-insurance event 3D dataof the insured asset(s). The insurance event may include events thatcause water, fire, smoke, wind, or hail damage to a home, vehicle,personal article, or other insured asset. For instance, thepost-insurance event 3D data may reveal an amount and depth of haildents or hail damage to a vehicle, or to the siding or roofing of ahome.

The post-insurance event 3D data may be compared 1514 with a baseline orinitial condition 3D data of the insured asset(s). The method 1500 mayfurther include determining 1516 an estimated repair or replacement costfor the insured asset(s). The method 1500 may also include preparing1518 a proposed virtual insurance claim for the insured's review, andtransmitting the proposed virtual insurance claim to their mobile devicefor display, and their review, modification, or approval. The method1500 may include additional, less, or alternate actions, including thosediscussed elsewhere herein.

FIG. 16 depicts another exemplary computer-implemented method ofestimating repair and/or replacement costs for insured assets using 3Ddata 1600. The method 1600 may include receiving post-insurance event 3Ddata of the insured asset(s) 1602. The insurance event may includeevents that cause water, fire, smoke, wind, or hail damage to a home,vehicle, personal article, or other insured asset. For instance, thepost-insurance event 3D data may indicate an amount of smoke damage to ahome, an amount of hail damage to a vehicle, or an amount of hail damageto the roof of a home.

The method may include analyzing 1602 the post-insurance event 3D datato identify insured asset features, and comparing 1604 thepost-insurance event 3D data to a baseline or expected 3D data todetermine 1606 an extent of damage to the insured asset(s) and/orfeature(s) identified. For instance, the damage may be hail, wind,water, fire, or smoke damage to personal articles, vehicles, or homes.

The method 1600 may further include determining 1608 an estimated repairor replacement cost for the insured asset(s). The method 1600 may alsoinclude preparing 1610 a proposed virtual insurance claim for theinsured's review, and transmitting the proposed virtual insurance claimto their mobile device for display, and their review, modification, orapproval. The method 1600 may include additional, less, or alternateactions, including those discussed elsewhere herein, including thatdiscussed with respect to FIG. 15.

Exemplary Use of Mobile Photogrammetry System and Structural AnalysisComputing Device

FIGS. 17-19 depict one example use of a mobile photogrammetry system1700 including a drone 1710 for capturing 3D images of an object foranalysis. FIG. 17 depicts an exemplary mobile photogrammetry system 1700including a structural analysis computing device 1702 mounted to and/orintegral to a drone 1710; FIG. 18 illustrates a side view of aneighborhood that may be analyzed by mobile photogrammetry system 1700;and FIG. 19 illustrates a cross-sectional side view of a building thatmay be analyzed by mobile photogrammetry system 1700. Mobilephotogrammetry system 1700 may further include one or more additionalstructural analysis computing device(s) 102, an insurance server 112(shown in FIG. 1), a user computing device 1704, and a navigation system1706. Mobile photogrammetry system 1700 may be similar to mobilephotogrammetry system 100 (shown in FIG. 1) and/or mobile photogrammetrysystem 1400 (shown in FIG. 14). In other embodiments, system 1700 mayinclude additional, fewer, or alternative components, including thosedescribed elsewhere herein.

In the exemplary embodiment, drone 1710 is positioned near or within acoverage zone 1712. Coverage zone 1712 is an area including one or moreproperties. The properties may include, but are not limited to,buildings, land, and/or objects located within the buildings or on theland. In the exemplary embodiment, each property may be associated withan owner or an owning party and an insurance policy. Coverage area 1712may be, for example, a building, a neighborhood, a city block, and/or aplot of land (e.g., owned land including any building on the ownedland). Coverage area 1712 may divided into smaller zones (not shown) formore precise navigation of drone 1710.

In the exemplary embodiment, structural analysis computing device 1702is mounted to and/or integral to a drone 1710. Accordingly, where theterm “drone” is used herein below, it refers to this “subsystem” of adrone and a computing device. Drone 1710 may include a processor 1720, amemory device 1722 in communication with processor 1720, and/or one ormore sensors 1724. Drone 1710 may be configured to move autonomously,semi-autonomously, and/or manually. Drone 1710 may be any kind of land,nautical, or aeronautical drone. For exemplary purposes only and withoutlimitation, drone 1710 is referred to herein as an aeronautical drone.That is, drone 1710 may be configured to travel by flying.

Sensors 1724 may include one or more object sensors 1724. Object sensors1724 may be configured to capture 3D image data of coverage area 1712 asdescribed elsewhere herein. Sensors 1724 may additionally include anytype of sensor such as a camera, a video recorder, a thermal camera, arange sensor, temperature sensor, moisture sensor, smoke detector,luminosity sensor, radiation detector, motion detector, pressure sensor,an audio recorder, and/or other types of sensors. Sensors 1724 and/orprocessor 1720 may be configured to collect, without limitation, 2Dimage data, 3D image data, video data, thermal image data, positioningdata, temperature data, time data, moisture data, smoke data, luminositydata, radiation data, motion data, pressure data, and/or audio data. Inthe exemplary embodiment, processor 1720 may control the operation ofsensors 1724. In other embodiments, sensors 1724 may include a processorand/or memory device (not shown) to capture and process sensor dataautonomous of processor 1720. Each sensor 1724 may be operatedindependently or dependently of other sensors 1724. Sensors 1724 mayinclude user-defined settings to control the operation of sensors 124.Sensors 1724 may be the same type of sensor (e.g., two object sensors)or different types of sensors. In some embodiments, sensors 1724 maysend the captured data to processor 1720 for data processing (e.g.,processing image data). In some embodiments, processor 1720 transmitscaptured data to structural analysis computing device 102 and/or usercomputing device 1704 for further processing.

In the exemplary system, drone 1710 may also include an object detector1726. Object detector 1726 is configured to identify objects near drone1710. In some embodiments, object detector 1726 may include a sonardetector, a radar detector, an ultrasonic detector, and/or anotherwaveform detector. As described herein, drone 1710 may be configured todetect objects alter or update a travel path of drone 1710 to avoid thedetected objects.

In the exemplary embodiment, drone 1710 may be deployable from a controlcenter 1728. Control center 1728 may be positioned near or withincoverage area 1712 to facilitate deployment of drone 1710 at coveragearea 1712. Control center 1728 may be configured to support, charge,and/or communicate with drone 1710. In at least some embodiments,control center 1728 is a separate computing device from drone 1710 thatincludes a processor and a memory device (both not shown). Controlcenter 1728 may be configured to generate control signals to operatedrone 1710. Control center 1728 may be configured to perform and/orcause drone 1710 to perform at least some of the functions describedherein. For example, control center 1728 may be in communication withone or more computing devices of system 1700 (e.g., structural analysiscomputing device 102 or insurance server 112) and provide drone 1710with control signals or data received from the computing devices.

In the exemplary embodiment, navigation system 1706 may be incommunication with drone 1710. Navigation system 1706 may be one or morecomputing devices configured scan a geographical region includingcoverage area 1712, generate navigational data, and provide thenavigational data to drone 1710. The navigation data may include, forexample, a map of the geographical region, obstacles within the region,and/or location data. In the exemplary embodiment, drone 1710 may beidentifiable by navigation system 1706 during scanning and navigationsystem 1706 may transmit navigation data include the location of drone1710 relative to the geographic region and/or coverage area 1712.Navigation system 1706 may be, but is not limited to, a GlobalPositioning System (GPS), a Global Navigation Satellite System (GNSS),and/or another position or navigation system. In another example, ifcoverage area 1712 is a building, navigation system 1706 may include twoor more position sensors (not shown in FIG. 17) in communication withdrone 1710. Each position sensor may determine a position of drone 1710relative to the respective position sensor and transmits the determinedposition to drone 1710. Drone 1710 may therefore be configured todetermine where drone 1710 is located within coverage area 1712 basedupon each determined position from the position sensors.

In the exemplary embodiment, drone 1710 may be in communication withstructural analysis computing device 102 and/or user computing device1704. Structural analysis computing device 102 and/or user computingdevice 1704 may be associated with an owner or other party related toone or more properties within coverage area 1712 (e.g., an owner of anobject being analyzed by drone 1710). In some embodiments, structuralanalysis computing device 102 and/or user computing device 1704 may beassociated with an insurance policy holder of a property within coveragearea 1712. User computing device 1704 may include, for example, acomputer, a laptop, a tablet, a smartphone, and/or a kiosk terminal.User computing device 1712 may include a mobile device (such as asmartphone, laptop, tablet, phablet, wearable electronics, smartglasses, smart watch or bracelet, personal digital assistant, pager, orother mobile computing device or mobile device configured for wirelesscommunication and/or data transmission). Structural analysis computingdevice 102 and/or user computing device 1712 may be configured toreceive the sensor data from drone 1710 to enable the user to review thecaptured 3D image data. Structural analysis computing device 102 and/oruser computing device 1712 may be further configured to transmit controlinput to drone 1710 to adjust how drone 10 operates.

Insurance server 112 may be in communication with drone 1710, structuralanalysis computing device 102, and/or user computing device 1704 toreceive captured and/or analyzed 3D image data. In some embodiments,system 100 may include a plurality of insurance servers 112. At leastone insurance server 112 is associated with an insurance provider thatmay be providing an insurance policy for one or more objects withincoverage area 1712. Based upon the sensor data, insurance server 112 maydetermine whether or not an insurance policy holder is eligible for oneor more insurance activities (e.g., generating an insurance quote,generating an insurance claim, adjusting an insurance policy, providinga discount, and/or other activities as described herein). If theinsurance policy holder is eligible, insurance server 112 may beconfigured to automatically initiate the insurance activity. Forexample, insurance server 112 may automatically populate an insuranceclaim for using information from 3D image data captured using drone 1710and transmitted to insurance server 112.

In the exemplary embodiment, system 100 may be configured to deploydrone 1710 to capture 3D image(s) of one or more objects (e.g., homes,vehicles, etc.) within coverage area 1712. The 3D images may becollected by drone 1710 and may indicate that damage may have occurredto the one or more objects within coverage 1712. Structural analysiscomputing device 102, user computing device 1704, and/or insuranceserver 112 may analyze the captured 3D images to estimate an amount ofdamage done to the object(s), a nature of the damage done, and/or aclaim disbursement amount, as described elsewhere herein.

In one embodiment, structural analysis computing device 102, usercomputing device 1704, and/or insurance server 112 may be configured totransmit an instruction to drone 1710 to navigate to a particular objectwithin coverage area 1710 to capture 3D image data thereof. Theinstruction may include a navigation path to the object (e.g., to theobject from control center 1728). In at least some embodiments, drone1710 may store a map of coverage area 1712 that may include informationsuch as potential obstacles, points of entry to the object, and/or namesof the objects within coverage area 1712. Drone 1710 may also receivethe navigation data from navigation system 1706 to determine thenavigation path. Drone 1710 may deploy from control center 1728 andautomatically travel along the determined navigation path throughcoverage area 1712. As drone 1710 travels, drone 1710 may be configuredto receive additional navigation data from navigation system 1706 toautomatically adjust its movement and/or the navigation path. In certainembodiments, object detectors 1726 may be configured to identify nearbyobjects, and drone 1710 may update the navigation path to avoid objectsthat may potentially block the navigation path. For example, if a dooris closed that blocks the navigation path, drone 1710 may update thenavigation path to circumvent the closed door.

In at least some embodiments, structural analysis computing device 102,user computing device 1704, and/or insurance server 112 may beconfigured to transmit control inputs to drone 1710 to navigate drone1710 through coverage area 1712 manually. In some embodiments, drone1710 may be configured to switch between automated and manual control ofnavigation. For example, drone 1710 may automatically travel along thenavigation path until an obstacle is reached and user computing device1704 may transmit control inputs to drone 1710 to navigate around theobstacle.

Once drone 1710 reaches the object, drone 1710 may be configured tocollect sensor data thereof (e.g., 3D image data) using sensors 1724. Insome embodiments, drone 1710 may store previous image data of the objectand may compare the captured 3D image data to the stored image todetermine whether the object has been damaged. Drone 1710 may beconfigured to identify features of the object that have been damaged. Insome embodiments, structural analysis computing device 102, usercomputing device 1704, and/or insurance server 112 may be configured totransmit control inputs to drone 1710 to operate sensors 1724.

The captured sensor data may be transmitted to structural analysiscomputing device 102, user computing device 1704, and/or insuranceserver 112 for review, as described elsewhere herein. In one embodiment,drone 1710, structural analysis computing device 102, and/or usercomputing device 1704 may be configured to transmit the captured sensordata to insurance server 112 to initiate one or more insuranceactivities.

Once drone 1710 has finished collecting sensor data, drone 1710 may beconfigured to navigate to another object within coverage area 1712 tocollect more sensor data or back to control center 1728. In someembodiments, when a power supply (not shown) of drone 1170 is reducedbelow a threshold value, drone 1710 may automatically return to controlcenter 1728. Drone 1710 may determine the navigation path to the nextobject or to control center 1728 by analyzing the stored map of coveragearea 1712, the navigation data from navigation system 1706, and/orinformation received from object detector 1726. In some embodiments,control center 1728 may be configured to guide drone 1710 back tocontrol center 1728. Once drone 1710 reaches control center 1728, drone1710 may dock and await further deployment instructions.

Turning now to FIG. 18, a neighborhood 1800 (i.e., a coverage area suchas coverage area 1712) is illustrated. Neighborhood 1800 includes aplurality of objects 1822, namely homes or properties. Mobilephotogrammetry system 1700 may be used to capture and analyze 3D imagesof objects 1822. In the exemplary embodiment, drone 1710 may be anaerial drone deployable from control center 1728. Control center 1728may be positioned within or near neighborhood 1800. Drone 1710 may beconfigured to travel around neighborhood 1800 and collect 3D images ofobjects 1822. User computing device 1704 (and/or structural analysiscomputing device 102 and/or insurance server 112, not shown in FIG. 18)may be operated by a user associated with neighborhood 1800. Forexample, user computing device 1704 may be operated by an owner of oneof objects 1822, a party maintaining system 1700, a party managingneighborhood 1800 (i.e., a local government), and/or another party. Usercomputing device 1704 may transmit instructions to drone 1710 foroperation and deployment thereof, as described herein.

Turning now to FIG. 19, a building 1900 (i.e., a coverage area such ascoverage area 1712) is illustrated. Building 1900 including a pluralityof objects 1922, such as rooms, features, and/or articles/objects withinbuilding 1900. Drone 1710 may be deployable from control center 1728. Inthe exemplary embodiment, control center 1728 may be positioned withinbuilding 1900. Navigation system 1706 may include two or more navigationbeacons 1713. In the exemplary embodiment, navigation beacons 1713 maybe positioned within building 1900. In other embodiments, navigationbeacons 1713 may be positioned at a different location. Navigationbeacons 1713 may be in communication with drone 1710. Navigation beacons1713 may be configured to broadcast position data relative to a positionof drone 1710. Drone 1710 may be configured to receive the position datafrom each navigation beacon 1713 to determine its position withinbuilding 1900. User computing device 1704 (and/or structural analysiscomputing device 102 and/or insurance server 112, not shown in FIG. 18)may be associated with an owner of building 1900. User computing device1704 may transmit instructions to drone 1710 for operation anddeployment thereof, as described herein.

Exemplary Home Feature Repair/Replacement Cost Methods

In one aspect, a computer-implemented method of estimating a repair orreplacement cost for home features may be provided. The method mayinclude (1) receiving, via one or more processors (and/or associatedtransceivers, such as via wireless communication or data transmission),3D data (or 3D image data) of a room of a structure after aninsurance-related event has occurred (e.g., event that causes fire,smoke, water, hail, wind, or other damage to the structure) that isacquired or generated by a 3D laser or light (or other) scanner (such asa 3D scanner associated with a mobile device (e.g., smart phone ortablet)); (2) determining or identifying, via the one or moreprocessors, room (or home) features based upon computer analysis (suchas via object recognition and/or optical character recognitiontechniques, or machine learning or pattern recognition techniques) ofthe 3D data from the 3D scanner; (3) determining or estimating, via theone or more processors, the type, dimensions, and/or manufacturer of theroom features based upon computer analysis (such as via objectrecognition and/or optical character recognition techniques, or machinelearning or pattern recognition techniques) of the 3D data from the 3Dscanner; (4) determining or estimating, via the one or more processors,an extent of damage to the room and/or room features caused by theinsurance-related event based upon computer analysis (such as via objectrecognition and/or optical character recognition techniques, or machinelearning or pattern recognition techniques) of the 3D data from the 3Dscanner; (5) determining, via the one or more processors, an estimatedrepair or replacement cost of the room and/or the room features basedupon (i) the type, dimensions, and/or manufacturer of the room features,and/or (ii) the extent of damage to the room and/or room features causedby the insurance-related event determined, at least in part, fromcomputer analysis of the 3D data of the room; and/or (6) transmitting,via the one or more processors (and/or associated transceivers, such asvia wireless communication or data transmission), the estimated repairor replacement cost of the room and/or room features to a mobile deviceof a customer for their review, modification, or approval.

The method may include preparing, via the one or more processors, aproposed insurance claim based upon the estimated repair or replacementcost of the room and/or room features; and/or transmitting, via the oneor more processors (and/or transceivers), the proposed insurance claimto the mobile device of the customer for their review, modification, orapproval.

The room feature and/or type of room feature may be one or more of: roomtype; ceiling type; window type; window subtype; door or doorway type orsubtype; and/or staircase type. The room feature may be one of, orassociated with, paneling, windows, ceilings, flooring, cabinetry,countertops, fireplaces, appliances (refrigerator, dish washer, oven,clothes washer or dryer, etc.), or lighting, and the type is one of, orassociated with, paneling, windows, ceilings, flooring, cabinetry,countertops, fireplaces, appliances, or lighting type or kind,respectively. The manufacturer may be one of, or associated with, apaneling, windows, ceilings, flooring, cabinetry, countertops,fireplaces, appliances, or lighting manufacturer, respectively.

The dimensions of the room feature may include paneling, window,ceiling, flooring, cabinetry, countertop, fireplace, appliance, orlighting dimensions, respectively. The extent of damage estimated mayinclude estimated dimensions of a damaged area within the room, orestimated dimensions of a damaged room feature (such as an area or sizeof paneling, windows, ceiling, flooring, cabinetry, countertops, orappliances that need to be replaced, for instance, due to smoke, fire,or water damage).

In another aspect, a computer-implemented method of estimating a repairor replacement cost for home features may be provided. The method mayinclude (1) receiving, via one or more processors (and/or associatedtransceivers, such as via wireless communication or data transmission),3D data (or 3D image data) of a room of a structure after aninsurance-related event has occurred (e.g., event that causes fire,smoke, water, hail, wind, or other damage to the structure) that isacquired or generated by a 3D laser or light (or other) scanner (such asa 3D scanner associated with a mobile device (e.g., smart phone ortablet)); (2) determining, via the one or more processors, roomdimensions of the room based upon computer analysis of the 3D data; (3)generating, via the one or more processors, a virtual depiction of theroom based upon the 3D data and/or room dimensions determined from the3D data, the virtual depiction of the room including the room dimensionssuperimposed on the virtual depiction of the room; (4) determining oridentifying, via the one or more processors, room (or home) featuresbased upon computer analysis (such as via object recognition and/oroptical character recognition techniques, or machine learning or patternrecognition techniques) of the 3D data from the 3D scanner; (5)determining or estimating, via the one or more processors, the type,dimensions, and/or manufacturer of the room features based upon computeranalysis (such as via object recognition and/or optical characterrecognition techniques, or machine learning or pattern recognitiontechniques) of the 3D data from the 3D scanner; (6) determining orestimating, via the one or more processors, an extent of damage to theroom and/or room features caused by the insurance-related event basedupon computer analysis (such as via object recognition and/or opticalcharacter recognition techniques, or machine learning or patternrecognition techniques) of the 3D data from the 3D scanner; (7)determining, via the one or more processors, an estimated repair orreplacement cost for the home, room, and/or room features based upon (i)the type, dimensions, and/or manufacturer of the room features, and/or(ii) the extent of damage caused by the insurance-related eventdetermined, at least in part, from computer analysis of the 3D data ofthe room; and/or (8) transmitting, via the one or more processors(and/or associated transceivers, such as via wireless communication ordata transmission), the estimated repair or replacement cost of thehome, room, and/or room features to a mobile device of a customer fortheir review, modification, or approval. The method may includepreparing, via the one or more processors, a proposed insurance claimbased upon the estimated repair or replacement cost of the home, room,and/or room features; and/or transmitting, via the one or moreprocessors (and/or transceivers), the proposed insurance claim to themobile device of the customer for their review, modification, orapproval.

In another aspect, a computer-implemented method of estimating a repairor replacement cost for home features may be provided. The method mayinclude (1) receiving, via one or more processors (and/or associatedtransceivers, such as via wireless communication or data transmission),3D data (or 3D image data) of a room of a structure after aninsurance-related event has occurred (e.g., event that causes fire,smoke, water, hail, wind, or other damage to the structure) that isacquired or generated by a 3D laser or light (or other) scanner (such asa 3D scanner associated with a mobile device (e.g., smart phone ortablet)); (2) determining, via the one or more processors, roomdimensions of the room based upon computer analysis of the 3D data; (3)determining or identifying, via the one or more processors, room (orhome) features based upon computer analysis (such as object recognitionand/or optical character recognition techniques, or machine learning orpattern recognition techniques) of the 3D data from the 3D scanner; (4)determining or estimating, via the one or more processors, the type,dimensions, and/or manufacturer of the room features based upon computeranalysis (such as via object recognition and/or optical characterrecognition techniques, or machine learning or pattern recognitiontechniques) of the 3D data from the 3D scanner; (5) determining orestimating, via the one or more processors, an extent of damage to thehome, room and/or room features caused by the insurance-related eventbased upon computer analysis (such as via object recognition and/oroptical character recognition techniques, or machine learning or patternrecognition techniques) of the 3D data from the 3D scanner; (6)generating, via the one or more processors, a virtual depiction of theroom based upon the 3D data and/or room dimensions determined from the3D data, the virtual depiction of the room including (a) the roomdimensions, and/or (b) type, dimensions, and/or manufacturer of the roomfeatures superimposed on the virtual depiction of the room, and (c) agraphical representative of the extent of damage to the home, room,and/or room features; (7) determining, via the one or more processors,an estimated repair or replacement cost for the home, room, or roomfeatures based upon (i) the type, dimensions, and/or manufacturer of theroom features, and/or (ii) the extent of damage caused by theinsurance-related event determined, at least in part, from computeranalysis of the 3D data of the room; and/or (8) transmitting, via theone or more processors (and/or associated transceivers, such as viawireless communication or data transmission), the estimated repair orreplacement cost of the home, room, and/or room features to a mobiledevice of a customer for their review, modification, or approval.

The method may include preparing, via the one or more processors, aproposed insurance claim based upon the estimated repair or replacementcost of the home, room, and/or room features; and/or transmitting, viathe one or more processors (and/or transceivers), the proposed insuranceclaim to the mobile device of the customer for their review,modification, or approval.

In another aspect, a computer-implemented method of estimating a repairor replacement cost for home features may be provided. The method mayinclude (1) receiving, via one or more processors (and/or transceivers,such as via wireless communication or data transmission), 3D data (or 3Dimage data) of a room of a structure acquired or generated by a 3D laseror light (or other) scanner (such as a 3D scanner associated with amobile device (e.g., smart phone or tablet)); (2) determining, via theone or more processors, room dimensions of the room based upon computeranalysis of the 3D data; (3) generating, via the one or more processors,a virtual depiction of the room based upon the 3D and/or room dimensionsdetermined from the 3D data, the virtual depiction of the room includingthe room dimensions superimposed on the virtual depiction of the room;(4) determining or identifying, via the one or more processors, room (orhome) features based upon computer analysis (such as via objectrecognition and/or optical character recognition techniques, or machinelearning or pattern recognition techniques) of the 3D data from the 3Dscanner; (5) determining or estimating, via the one or more processors,the type, dimensions, and/or manufacturer of the room features basedupon computer analysis (such as via object recognition and/or opticalcharacter recognition techniques, or machine learning or patternrecognition techniques) of the 3D data from the 3D scanner; and/or (6)determining, via the one or more processors, an estimated repair orreplacement cost of the home, room, and/or room features based upon thetype, dimensions, and/or manufacturer determined, at least in part, fromcomputer analysis of the 3D data of the room.

The method may include adding, via the one or more processors, the roomto a virtual representation of the home associated with the user; and/oradding the repair or replacement cost for the room and/or room featuresto a total repair or replacement cost associated with all rooms withinthe home. The method may include generating, via the one or moreprocessors, a quote for homeowners insurance based upon the total repairor replacement cost generating, and transmitting, via the one or moreprocessors (and/or associated transceivers, such as via wirelesscommunication or data transmission), the quote to the user's mobiledevice for display thereon and their review, modification, or approvalto facilitate providing more accurate insurance pricing.

The method may include receiving, via the one or more processors (and/orassociated transceivers), post-insurance event 3D data of the roomgenerated by a 3D scanner from the user's mobile device; comparing, viathe one or more processors, the 3D data with the post-insurance event 3Ddata post-insurance event 3D data to determine an amount of damage tothe home, room, and/or room features; generating, via the one or moreprocessors, an estimated repair or replacement cost for the home, room,and/or room features based upon the comparison; generating, via the oneor more processors, a proposed insurance claim for an insured based uponthe estimated repair or replacement cost; and/or transmitting, via theone or more processors (and/or associated transceivers), the proposedinsurance claim to the insured's mobile device for their review,modification, or approval.

The method may include preparing, via the one or more processors, aproposed insurance claim based upon the estimated repair or replacementcost of the home, room, and/or room features; and transmitting, via theone or more processors (and/or transceivers), the proposed insuranceclaim to the mobile device of the customer for their review,modification, or approval. The extent of damaged estimated includesestimated dimensions of a damaged area within the room, or estimateddimensions of a damaged room feature (such as an area of paneling,ceiling, flooring, cabinetry, or countertops that need to be replaced,for instance, due to water, smoke, or fire damage).

The foregoing methods may include additional, less, or alternateactions, including those discussed elsewhere herein. Additionally oralternatively, the foregoing methods may be implemented via one or morelocal or remote processors and/or transceivers, and/or viacomputer-executable instructions stored on non-transitorycomputer-readable media or medium.

Exemplary Personal Articles Repair/Replacement Cost

In another aspect, a computer-implemented method of estimating a repairor replacement cost for one or more personal articles may be provided.The method may include (1) receiving, via one or more processors (and/orassociated transceivers, such as via wireless communication or datatransmission), 3D data (or 3D image data) of a personal article (orpersonal belonging) acquired via, or generated by, a 3D laser or light(or other) scanner (such as a 3D scanner associated with a mobile device(e.g., smart phone or tablet)); (2) determining or identifying, via theone or more processors, (i) the personal article, and/or (ii) featuresof the personal article based upon computer analysis (such as objectrecognition and/or optical character recognition techniques, or machinelearning or pattern recognition techniques) of the 3D data from the 3Dscanner (for instance by comparing the 3D data of the personal articlewith a virtual catalog known items); (3) determining or estimating, viathe one or more processors, the type and/or manufacturer of the personalarticle based upon computer analysis (such as object recognition and/oroptical character recognition techniques, or machine learning or patternrecognition techniques) of the 3D data from the 3D scanner; and/or (4)determining, via the one or more processors, an estimated repair orreplacement cost for the personal article based upon (i) the personalarticle, (ii) features of the personal article, (iii) type of thepersonal article, and/or (iv) manufacturer of the personal articledetermined, at least in part, from computer analysis of the 3D data ofthe room.

The method may include adding, via the one or more processors, thepersonal article to an inventory list associated with the user; and/oradding, via the one or more processors, the repair or replacement costfor the personal article to a total repair or replacement costassociated with all personal articles including within the inventorylist. The method may include adding, via the one or more processors, thepersonal article to a virtual inventory list associated with the user;adding, via the one or more processors, the repair or replacement costfor the personal article to a total repair or replacement costassociated with all personal articles including within the virtualinventory list; generating, via the one or more processors, a virtualquote for personal articles insurance based upon the total repair orreplacement cost; and/or transmitting, via the one or more processors(and/or associated transceivers, such as via wireless communication ordata transmission), the virtual quote for personal articles insurance toa mobile device of a user for their review, modification, or approval tofacilitate providing a more accurate assessment of risk to personalbelongings and providing more appropriate insurance coverage tocustomers.

The foregoing method may include additional, less, or alternate actions,including those discussed elsewhere herein. Additionally oralternatively, the foregoing method may be implemented via one or morelocal or remote processors and/or transceivers, and/or viacomputer-executable instructions stored on non-transitorycomputer-readable media or medium.

Exemplary Vehicle Repair/Replacement Cost Methods

In another aspect a computer-implemented method of estimating a repairor replacement cost for vehicle and/or vehicle features may be provided.The method may include (1) receiving, via one or more processors (and/orassociated transceivers, such as via wireless communication or datatransmission), 3D data (or 3D image data) of a vehicle after aninsurance-related event has occurred (e.g., event that causes body,fire, smoke, water, hail, wind, or other damage to the vehicle) that isacquired or generated by a 3D laser or light (or other) scanner (such asa 3D scanner associated with a mobile device (e.g., smart phone ortablet)); (2) determining or identifying, via the one or moreprocessors, a type of vehicle, vehicle manufacturer, vehicle age, and/orvehicle features based upon computer analysis (such as via objectrecognition and/or optical character recognition techniques, or machinelearning or pattern recognition techniques) of the 3D data from the 3Dscanner; (3) determining or estimating, via the one or more processors,an extent of damage to the vehicle or vehicle features caused by theinsurance-related event based upon computer analysis (such as via objectrecognition and/or optical character recognition techniques, or machinelearning or pattern recognition techniques) of the 3D data from the 3Dscanner (such as determining dimensions of body damage, number ofwindows damaged, number of hail dents in the body, size of each haildent in the body of the vehicle, etc.); (4) determining, via the one ormore processors, an estimated repair or replacement cost of the vehicleand/or the vehicle features based upon (i) the type of vehicle, vehiclefeatures, and vehicle manufacturer, and/or (ii) the extent of damage tothe vehicle and/or vehicle features caused by the insurance-relatedevent determined, at least in part, from computer analysis of the 3Ddata of the room; and/or (5) transmitting, via the one or moreprocessors (and/or associated transceivers, such as via wirelesscommunication or data transmission), the estimated repair or replacementcost of the vehicle and/or vehicle features to a mobile device of acustomer for display and their review, modification, or approval.

The method may include preparing, via the one or more processors, aproposed insurance claim based upon the estimated repair or replacementcost of the vehicle and/or vehicle features; and/or transmitting, viathe one or more processors (and/or transceivers), the proposed insuranceclaim to the mobile device of the customer for their review,modification, or approval. The method may include receiving, via one ormore processors (and/or associated transceivers, such as via wirelesscommunication or data transmission), 3D data (or 3D image data) of aninjured passenger or driver after the insurance-related event hasoccurred (e.g., vehicle crash) that is acquired or generated by a 3Dlaser or light (or other) scanner (such as a 3D scanner associated witha mobile device (e.g., smart phone or tablet)); determining orestimating, via the one or more processors, an extent or severity ofinjuries to the injured person caused by the insurance-related eventbased upon computer analysis of the 3D data from the 3D scanner; and/orif the extent or severity of injuries requires medical attention,requesting, via the one or more processors (and/or transceivers), thatmedical personal or an ambulance travel to the scene of the vehiclecrash and provide medical attention.

In another aspect, a computer-implemented method of estimating a repairor replacement cost for vehicle or vehicle feature may be provided. Themethod may include (1) receiving, via one or more processors (and/orassociated transceivers, such as via wireless communication or datatransmission), 3D data (or 3D image data) of a vehicle acquired via, orgenerated by, a 3D laser or light (or other) scanner (such as a 3Dscanner associated with a mobile device (e.g., smart phone or tablet));(2) determining or identifying, via the one or more processors, (i) thevehicle, and/or (ii) features of the vehicle based upon computeranalysis (such as object recognition and/or optical characterrecognition techniques, or machine learning or pattern recognitiontechniques) of the 3D data from the 3D scanner (for instance bycomparing the 3D data of the vehicle with a virtual catalog knownvehicles); (3) determining or estimating, via the one or moreprocessors, the type and/or manufacturer of the vehicle based uponcomputer analysis (such as object recognition and/or optical characterrecognition techniques, or machine learning or pattern recognitiontechniques) of the 3D data from the 3D scanner; and/or (4) determining,via the one or more processors, an estimated repair or replacement costfor the vehicle based upon (i) the vehicle, (ii) features of thevehicle, (iii) type of vehicle, and/or (iv) manufacturer of the vehicledetermined, at least in part, from computer analysis of the 3D data ofthe room. The method may include generating, via the one or moreprocessors, a virtual quote for auto insurance based upon the totalrepair or replacement cost; and/or transmitting, via the one or moreprocessors (and/or associated transmitters), the virtual quote to amobile device of a customer for their review, modification, or approval.

The foregoing methods may include additional, less, or alternateactions, including those discussed elsewhere herein. Additionally oralternatively, the foregoing methods may be implemented via one or morelocal or remote processors and/or transceivers, and/or viacomputer-executable instructions stored on non-transitorycomputer-readable media or medium.

Exemplary Computer Systems for Determining Repair or Replacement Costfor Home Features

In one aspect, a computer system for estimating a repair or replacementcost for home features may be provided. The computer system may includeone or more processors and/or transceivers configured to: (1) receive,via wireless communication or data transmission, 3D data (or 3D imagedata) of a room of a structure after an insurance-related event hasoccurred (e.g., event that causes fire, smoke, water, hail, wind, orother damage to the structure) that is acquired or generated by a 3Dlaser or light (or other) scanner (such as a 3D scanner associated witha mobile device (e.g., smart phone or tablet)); (2) determine oridentify room (or home) features based upon computer analysis (such asvia object recognition and/or optical character recognition techniques,or machine learning or pattern recognition techniques) of the 3D datafrom the 3D scanner; (3) determine or estimate the type, dimensions,and/or manufacturer of the room features based upon computer analysis(such as via object recognition and/or optical character recognitiontechniques, or machine learning or pattern recognition techniques) ofthe 3D data from the 3D scanner; (4) determine or estimate an extent ofdamage to the room and/or room features caused by the insurance-relatedevent based upon computer analysis (such as via object recognitionand/or optical character recognition techniques, or machine learning orpattern recognition techniques) of the 3D data from the 3D scanner; (5)determine an estimated repair or replacement cost of the room and/or theroom features based upon (i) the type, dimensions, and/or manufacturerof the room features, and/or (ii) the extent of damage to the roomand/or room features caused by the insurance-related event determined,at least in part, from computer analysis of the 3D data of the room;and/or (6) transmit, via wireless communication or data transmission,the estimated repair or replacement cost of the room and/or roomfeatures to a mobile device of a customer for display and their review,modification, or approval.

The one or more processors and/or transceivers may be further configuredto: prepare a proposed insurance claim based upon the estimated repairor replacement cost of the room and/or room features; and transmit theproposed insurance claim to the mobile device of the customer fordisplay and their review, modification, or approval. The room featuremay be one of, or associated with, paneling, windows, ceilings,flooring, cabinetry, countertops, fireplaces, appliances (refrigerator,dish washer, oven, clothes washer or dryer, etc.), or lighting. The typeof home or room feature may be one of, or associated with, paneling,windows, ceilings, flooring, cabinetry, countertops, fireplaces,appliances, or lighting type or kind, respectively. The manufacturer maybe one of, or associated with, a paneling, windows, ceilings, flooring,cabinetry, countertops, fireplaces, appliances, or lightingmanufacturer, respectively.

The extent of damage estimated may include estimated dimensions of adamaged area within the room, or estimated dimensions of a damaged roomfeature (such as an area or size of paneling, windows, ceiling,flooring, cabinetry, countertops, or appliances that need to bereplaced, for instance, due to smoke, fire, or water damage).

In another aspect, a computer system for estimating a repair orreplacement cost for room or home features may be provided. The computersystem may include one or more processors and/or transceivers configuredto: (1) receive, via wireless communication or data transmission, 3Ddata (or 3D image data) of a room of a structure after aninsurance-related event has occurred (e.g., event that causes fire,smoke, water, hail, wind, or other damage to the structure) that isacquired or generated by a 3D laser or light (or other) scanner (such asa 3D scanner associated with a mobile device (e.g., smart phone ortablet)); (2) determine room dimensions of the room based upon computeranalysis of the 3D data; (3) generate a virtual depiction of the roombased upon the 3D data and/or room dimensions determined from the 3Ddata, the virtual depiction of the room including the room dimensionssuperimposed on the virtual depiction of the room; (4) determine oridentify room (or home) features based upon computer analysis (such asvia object recognition and/or optical character recognition techniques,or machine learning or pattern recognition techniques) of the 3D datafrom the 3D scanner; (5) determine or estimate the type, dimensions,and/or manufacturer of the room features based upon computer analysis(such as via object recognition and/or optical character recognitiontechniques, or machine learning or pattern recognition techniques) ofthe 3D data from the 3D scanner; (6) determine or estimate an extent ofdamage to the room and/or room features caused by the insurance-relatedevent based upon computer analysis (such as via object recognitionand/or optical character recognition techniques, or machine learning orpattern recognition techniques) of the 3D data from the 3D scanner; (7)determine an estimated repair or replacement cost for the home, room,and/or room features based upon (i) the type, dimensions, and/ormanufacturer of the room features, and/or (ii) the extent of damagecaused by the insurance-related event determined, at least in part, fromcomputer analysis of the 3D data of the room; and/or (8) transmit, viawireless communication or data transmission, the estimated repair orreplacement cost of the home, room, and/or room features to a mobiledevice of a customer for their review, modification, or approval. Theone or more processors and/or transceivers may be further configured to:prepare a proposed insurance claim based upon the estimated repair orreplacement cost of the home, room, and/or room features; and/ortransmit the proposed insurance claim to the mobile device of thecustomer for their review, modification, or approval.

In another aspect, a computer system for estimating a repair orreplacement cost for a home or room feature. The computer system mayinclude one or more processors and/or transceivers configured to: (1)receive, via wireless communication or data transmission, 3D data (or 3Dimage data) of a room of a structure after an insurance-related eventhas occurred (e.g., event that causes fire, smoke, water, hail, wind, orother damage to the structure) that is acquired or generated by a 3Dlaser or light (or other) scanner (such as a 3D scanner associated witha mobile device (e.g., smart phone or tablet)); (2) determine roomdimensions of the room based upon computer analysis of the 3D data; (3)determine or identify room (or home) features based upon computeranalysis (such as object recognition and/or optical characterrecognition techniques, or machine learning or pattern recognitiontechniques) of the 3D data from the 3D scanner; (4) determine orestimate the type, dimensions, and/or manufacturer of the room featuresbased upon computer analysis (such as via object recognition and/oroptical character recognition techniques, or machine learning or patternrecognition techniques) of the 3D data from the 3D scanner; (5)determine or estimate an extent of damage to the home, room and/or roomfeatures caused by the insurance-related event based upon computeranalysis (such as via object recognition and/or optical characterrecognition techniques, or machine learning or pattern recognitiontechniques) of the 3D data from the 3D scanner; (6) generate a virtualdepiction of the room based upon the 3D data and/or room dimensionsdetermined from the 3D data, the virtual depiction of the room including(a) the room dimensions, and/or (b) type, dimensions, and/ormanufacturer of the room features superimposed on the virtual depictionof the room, and (c) a graphical representative of the extent of damageto the home, room, and/or room features; (7) determine an estimatedrepair or replacement cost for the home, room, or room features basedupon (i) the type, dimensions, and/or manufacturer of the room features,and/or (ii) the extent of damage caused by the insurance-related eventdetermined, at least in part, from computer analysis of the 3D data ofthe room; and/or (8) transmit, via wireless communication or datatransmission, the estimated repair or replacement cost of the home,room, and/or room features to a mobile device of a customer for theirreview, modification, or approval. The one or more processors and/ortransceivers may be further configured to: prepare a proposed insuranceclaim based upon the estimated repair or replacement cost of the home,room, and/or room features; and transmit the proposed insurance claim tothe mobile device of the customer for display thereon and their review,modification, or approval.

In another aspect, a computer system for estimating a repair orreplacement cost for a room or home feature may be provided. Thecomputer system may include one or more processors and/or transceiversconfigured to: (1) receive, via wireless communication or datatransmission, 3D data (or 3D image data) of a room of a structureacquired or generated by a 3D laser or light (or other) scanner (such asa 3D scanner associated with a mobile device (e.g., smart phone ortablet)); (2) determine room dimensions of the room based upon computeranalysis of the 3D data; (3) generate a virtual depiction of the roombased upon the 3D and/or room dimensions determined from the 3D data,the virtual depiction of the room including the room dimensionssuperimposed on the virtual depiction of the room; (4) determine oridentify room (or home) features based upon computer analysis (such asvia object recognition and/or optical character recognition techniques,or machine learning or pattern recognition techniques) of the 3D datafrom the 3D scanner; (5) determine or estimate the type, dimensions,and/or manufacturer of the room features based upon computer analysis(such as via object recognition and/or optical character recognitiontechniques, or machine learning or pattern recognition techniques) ofthe 3D data from the 3D scanner; and/or (6) determine an estimatedrepair or replacement cost of the home, room, and/or room features basedupon the type, dimensions, and/or manufacturer determined, at least inpart, from computer analysis of the 3D data of the room.

The one or more processors and/or transceivers may be further configuredto: add the room to a virtual representation of the home associated withthe user; and/or add the repair or replacement cost for the room and/orroom features to a total repair or replacement cost associated with allrooms within the home. The one or more processors and/or transceiversmay be further configured to: generate a quote for homeowners insurancebased upon the total repair or replacement cost generating, and/ortransmit, via wireless communication or data transmission, the quote tothe user's mobile device for their review, modification, or approval tofacilitate providing more accurate insurance pricing.

The one or more processors and/or transceivers may be further configuredto: receive post-insurance event 3D data of the room generated by a 3Dscanner from the user's mobile device; compare the 3D data with thepost-insurance event 3D data post-insurance event 3D data to determinean amount of damage to the home, room, and/or room features; generate anestimated repair or replacement cost for the home, room, and/or roomfeatures based upon the comparison; generate a proposed insurance claimfor an insured based upon the estimated repair or replacement cost;and/or transmit the proposed insurance claim to the insured's mobiledevice for display and their review, modification, or approval.

The one or more processors and/or transceivers may be further configuredto: prepare a proposed insurance claim based upon the estimated repairor replacement cost of the home, room, and/or room features; andtransmit the proposed insurance claim to the mobile device of thecustomer for display and their review, modification, or approval. Theextent of damaged estimated may include estimated dimensions of adamaged area within the room, or estimated dimensions of a damaged roomfeature (such as an area of paneling, ceiling, flooring, cabinetry, orcountertops that need to be replaced, for instance, due to water, smoke,or fire damage). The foregoing computer systems may include additional,less, or alternate functionality, including that discussed elsewhereherein.

Exemplary Personal Article Repair/Replacement Cost System

In one aspect, a computer system for estimating a repair or replacementcost for one or more personal articles may be provided. The computersystem comprising one or more processors and/or transceivers configuredto: (1) receive, via wireless communication or data transmission, 3Ddata (or 3D image data) of a personal article (or personal belonging)acquired via, or generated by, a 3D laser or light (or other) scanner(such as a 3D scanner associated with a mobile device (e.g., smart phoneor tablet)); (2) determine or identify (i) the personal article, and/or(ii) features of the personal article based upon computer analysis (suchas object recognition and/or optical character recognition techniques,or machine learning or pattern recognition techniques) of the 3D datafrom the 3D scanner (for instance by comparing the 3D data of thepersonal article with a virtual catalog known items); (3) determine orestimate the type and/or manufacturer of the personal article based uponcomputer analysis (such as object recognition and/or optical characterrecognition techniques, or machine learning or pattern recognitiontechniques) of the 3D data from the 3D scanner; and/or (4) determine anestimated repair or replacement cost for the personal article based upon(i) the personal article, (ii) features of the personal article, (iii)type of the personal article, and/or (iv) manufacturer of the personalarticle determined, at least in part, from computer analysis of the 3Ddata of the room.

The one or more processors and/or transceivers further configured to:add the personal article to a virtual inventory list associated with theuser; add the repair or replacement cost for the personal article to atotal repair or replacement cost associated with all personal articlesincluding within the virtual inventory list; generate a virtual quotefor personal articles insurance (or homeowners or renters insurance)based upon, at least in part, the total repair or replacement cost;and/or transmit, via wireless communication or data transmission, thevirtual quote for personal articles (or homeowners or renters) insuranceto a mobile device of a user for display and their review, modification,or approval to facilitate providing a more accurate assessment of riskto personal belongings and providing more appropriate insurance coverageto customers. The foregoing computer system may include additional,less, or alternate functionality, including that discussed elsewhereherein.

Exemplary Vehicle Repair/Replacement Cost Systems

In one aspect, a computer system for determining a repair and/orreplacement cost of a vehicle or vehicle features may be provided. Thecomputer system may include one or more processors and/or transceiversconfigured to: (1) receive, such as via wireless communication or datatransmission, 3D data (or 3D image data) of a vehicle after aninsurance-related event has occurred (e.g., event that causes body,fire, smoke, water, hail, wind, or other damage to the vehicle) that isacquired or generated by a 3D laser or light (or other) scanner (such asa 3D scanner associated with a mobile device (e.g., smart phone ortablet)); (2) determine or identify a type of vehicle, vehiclemanufacturer, vehicle age, and/or vehicle features based upon computeranalysis (such as via object recognition and/or optical characterrecognition techniques, or machine learning or pattern recognitiontechniques) of the 3D data from the 3D scanner; (3) determine orestimate an extent of damage to the vehicle or vehicle features causedby the insurance-related event based upon computer analysis (such as viaobject recognition and/or optical character recognition techniques, ormachine learning or pattern recognition techniques) of the 3D data fromthe 3D scanner (such as determining dimensions of body damage, number ofwindows damaged, number of hail dents in the body, size of each haildent in the body of the vehicle, etc.); (4) determine an estimatedrepair or replacement cost of the vehicle and/or the vehicle featuresbased upon (i) the type of vehicle, vehicle features, and vehiclemanufacturer, and/or (ii) the extent of damage to the vehicle and/orvehicle features caused by the insurance-related event determined, atleast in part, from computer analysis of the 3D data of the room; and/or(5) transmit, such as via wireless communication or data transmission,the estimated repair or replacement cost of the vehicle and/or vehiclefeatures to a mobile device of a customer for display and their review,modification, or approval.

The one or more processors and/or transceivers further configured to:prepare a proposed insurance claim based upon the estimated repair orreplacement cost of the vehicle and/or vehicle features; and/or transmitthe proposed insurance claim to the mobile device of the customer fortheir review, modification, or approval.

The one or more processors and/or transceivers may be further configuredto: receive, such as via wireless communication or data transmission, 3Ddata (or 3D image data) of an injured passenger or driver after theinsurance-related event has occurred (e.g., vehicle crash) that isacquired or generated by a 3D laser or light (or other) scanner (such asa 3D scanner associated with a mobile device (e.g., smart phone ortablet)); determine or estimate an extent or severity of injuries to theinjured person caused by the insurance-related event based upon computeranalysis of the 3D data from the 3D scanner; and/or if the extent orseverity of injuries requires medical attention, requesting, via the oneor more processors (and/or transceivers), that medical personal or anambulance travel to the scene of the vehicle crash and provide medicalattention.

In another aspect, a computer system for estimating a repair orreplacement cost for a vehicle or vehicle feature may be provided. Thecomputer system may include one or more processors and/or transceiversconfigured to: (1) receive, such as via wireless communication or datatransmission, 3D data (or 3D image data) of a vehicle acquired via, orgenerated by, a 3D laser or light (or other) scanner (such as a 3Dscanner associated with a mobile device (e.g., smart phone or tablet));(2) determine or identify (i) the vehicle, and/or (ii) features of thevehicle based upon computer analysis (such as object recognition and/oroptical character recognition techniques, or machine learning or patternrecognition techniques) of the 3D data from the 3D scanner (for instanceby comparing the 3D data of the vehicle with a virtual catalog knownvehicles); (3) determine or estimate the type and/or manufacturer of thevehicle based upon computer analysis (such as object recognition and/oroptical character recognition techniques, or machine learning or patternrecognition techniques) of the 3D data from the 3D scanner; and/or (4)determine an estimated repair or replacement cost for the vehicle basedupon (i) the vehicle, (ii) features of the vehicle, (iii) type ofvehicle, and/or (iv) manufacturer of the vehicle determined, at least inpart, from computer analysis of the 3D data of the room.

The one or more processors and/or transceivers may be configured to:generate a virtual quote for auto insurance based upon the total repairor replacement cost; and/or transmit the virtual quote to a mobiledevice of a customer for their review, modification, or approval. Theforegoing computer systems may include additional, less, or alternatefunctionality, including that discussed elsewhere herein.

ADDITIONAL CONSIDERATIONS

With the foregoing, an insurance customer may opt-in to a rewards,insurance discount, or other type of program. After the insurancecustomer provides their affirmative consent, an insurance provide 3Dscanner application and/or remote server may collect 3D data taken bythe insured using a 3D scanner. The 3D data may be associated withinsured assets, including before, during, and/or after aninsurance-related event, such as a home fire or vehicle collision. Inreturn, risk-averse drivers, and/or vehicle owners may receive discountsor insurance cost savings related to auto, home, life, personal articlesand other types of insurance from the insurance provider.

In one aspect, the 3D data may be collected or received by an insured'smobile device or a dedicated 3D scanner, and/or an insurance providerremote server, such as via direct or indirect wireless communication ordata transmission from an application running on the insured's mobiledevice, after the insured or customer affirmatively consents orotherwise opts-in to an insurance discount, reward, or other program.The insurance provider may then analyze the data received with thecustomer's permission to provide benefits to the customer. As a result,risk-averse customers may receive insurance discounts or other insurancecost savings based upon data that reflects low risk and/or technologythat mitigates or prevents risk to insured assets, such as homes,personal belongings, or vehicles.

Although not preferred, in addition to 3D scanning, some embodiments mayutilize 2D scanning or determining dimensions from 2D digital or otherimages. For instance, room dimensions may be determined from 2D images.

As will be appreciated based upon the foregoing specification, theabove-described embodiments of the disclosure may be implemented usingcomputer programming or engineering techniques including computersoftware, firmware, hardware or any combination or subset thereof. Anysuch resulting program, having computer-readable code means, may beembodied or provided within one or more computer-readable media, therebymaking a computer program product, i.e., an article of manufacture,according to the discussed embodiments of the disclosure. Thecomputer-readable media may be, for example, but is not limited to, afixed (hard) drive, diskette, optical disk, magnetic tape, semiconductormemory such as read-only memory (ROM), and/or any transmitting/receivingmedium such as the Internet or other communication network or link. Thearticle of manufacture containing the computer code may be made and/orused by executing the code directly from one medium, by copying the codefrom one medium to another medium, or by transmitting the code over anetwork.

These computer programs (also known as programs, software, softwareapplications, “apps”, or code) include machine instructions for aprogrammable processor, and can be implemented in a high-levelprocedural and/or object-oriented programming language, and/or inassembly/machine language. As used herein, the terms “machine-readablemedium” “computer-readable medium” refers to any computer programproduct, apparatus and/or device (e.g., magnetic discs, optical disks,memory, Programmable Logic Devices (PLDs)) used to provide machineinstructions and/or data to a programmable processor, including amachine-readable medium that receives machine instructions as amachine-readable signal. The “machine-readable medium” and“computer-readable medium,” however, do not include transitory signals.The term “machine-readable signal” refers to any signal used to providemachine instructions and/or data to a programmable processor.

As used herein, a processor may include any programmable systemincluding systems using micro-controllers, reduced instruction setcircuits (RISC), application specific integrated circuits (ASICs), logiccircuits, and any other circuit or processor capable of executing thefunctions described herein. The above examples are example only, and arethus not intended to limit in any way the definition and/or meaning ofthe term “processor.”

As used herein, the terms “software” and “firmware” are interchangeable,and include any computer program stored in memory for execution by aprocessor, including RAM memory, ROM memory, EPROM memory, EEPROMmemory, and non-volatile RAM (NVRAM) memory. The above memory types areexample only, and are thus not limiting as to the types of memory usablefor storage of a computer program.

In one embodiment, a computer program is provided, and the program isembodied on a computer readable medium. In an example embodiment, thesystem is executed on a single computer system, without requiring aconnection to a sever computer. In a further embodiment, the system isbeing run in a Windows® environment (Windows is a registered trademarkof Microsoft Corporation, Redmond, Wash.). In yet another embodiment,the system is run on a mainframe environment and a UNIX® serverenvironment (UNIX is a registered trademark of X/Open Company Limitedlocated in Reading, Berkshire, United Kingdom). The application isflexible and designed to run in various different environments withoutcompromising any major functionality. In some embodiments, the systemincludes multiple components distributed among a plurality of computingdevices. One or more components may be in the form ofcomputer-executable instructions embodied in a computer-readable medium.The systems and processes are not limited to the specific embodimentsdescribed herein. In addition, components of each system and eachprocess can be practiced independent and separate from other componentsand processes described herein. Each component and process can also beused in combination with other assembly packages and processes.

As used herein, an element or step recited in the singular and precededby the word “a” or “an” should be understood as not excluding pluralelements or steps, unless such exclusion is explicitly recited.Furthermore, references to “example embodiment” or “one embodiment” ofthe present disclosure are not intended to be interpreted as excludingthe existence of additional embodiments that also incorporate therecited features.

The patent claims at the end of this document are not intended to beconstrued under 35 U.S.C. § 112(f) unless traditionalmeans-plus-function language is expressly recited, such as “means for”or “step for” language being expressly recited in the claim(s).

This written description uses examples to disclose the disclosure,including the best mode, and also to enable any person skilled in theart to practice the disclosure, including making and using any devicesor systems and performing any incorporated methods. The patentable scopeof the disclosure is defined by the claims, and may include otherexamples that occur to those skilled in the art. Such other examples areintended to be within the scope of the claims if they have structuralelements that do not differ from the literal language of the claims, orif they include equivalent structural elements with insubstantialdifferences from the literal languages of the claims.

We claim:
 1. A structural analysis computing device for generating aninsurance claim for an object pictured in a three-dimensional (3D)image, the structural analysis computing device coupled to a drone, thestructural analysis computing device comprising: a memory; a userinterface; an object sensor configured to scan an interior structure ofa room to capture the 3D image of the room, wherein the room includes aplurality of objects; and at least one processor in communication withthe memory and the object sensor, wherein the at least one processor isprogrammed to: transmit an instruction to the drone to navigate to anobject of the plurality of objects; transmit an instruction to theobject sensor to capture the 3D image of the object; access the 3D imageof the object; analyze the 3D image captured by the drone to identifyfeatures of the object using image analysis trained using one or moremachine learning algorithms; automatically identify the object of theplurality of objects within the 3D image based upon the analysis;determine that the identified object is an insurable asset using adatabase lookup of insurable assets; in response to determining that theidentified object is one of the insurable assets, determine a nature andan extent of damage to a damaged feature of the object based on theanalysis; determine a cost of repair of the damaged feature of theobject based upon the nature and extent of the damage; generate a claimform including the determined cost of repair; and display the generatedclaim form to a user of the structural analysis computing device forreview and approval by the user.
 2. The structural analysis computingdevice of claim 1, wherein the structural analysis computing device isintegral to the drone.
 3. The structural analysis computing device ofclaim 1, wherein the processor is further programmed to transmit the 3Dimage of the object to an insurance server.
 4. The structural analysiscomputing device of claim 1, wherein the object sensor is configured tocapture the 3D image including an exterior of the object.
 5. Thestructural analysis computing device of claim 1, wherein the nature ofthe damage includes at least one of fire, smoke, water, hail, wind, andtheft.
 6. The structural analysis computing device of claim 1, whereinthe features of the object include at least one of a type of the object,a manufacturer of the object, and a component of the object, and whereinthe at least one processor is further programmed to determine the costof repair of the damaged feature based upon at least one of the type andmanufacturer of the object.
 7. The structural analysis computing deviceof claim 1, wherein the accessed 3D image is a post-damage 3D image, andwherein the at least one processor is further programmed to retrieve apre-damage 3D image from the memory.
 8. The structural analysiscomputing device of claim 7, wherein the at least one processor isfurther programmed to compare the post-damage 3D image to the pre-damage3D image to determine the extent of the damage to the damaged feature ofthe object.
 9. A computer-implemented method for generating an insuranceclaim for an object pictured in a three-dimensional (3D) image, using astructural analysis computing device including a memory, a userinterface, an object sensor configured to scan a plurality of objects tocapture the 3D image of the object, and at least one processor incommunication with the memory and the object sensor, the structuralanalysis computing device coupled to a drone, the method comprising:transmitting an instruction to the drone to navigate the object of theplurality of objects; transmitting an instruction to the object sensorto capture the 3D image of the object; accessing the 3D image includingthe object; analyzing the 3D images captured by the drone to identifyfeatures of the object using image analysis trained using one or moremachine learning algorithms; automatically identifying the object of theplurality of objects within the 3D image based upon the analysis;determining that the identified object is an insurable asset using adatabase lookup of insurable assets; in response to determining that theidentified Wept is one of the insurable assets, determining a nature andan extent of damage to a damaged feature of the object based on theanalysis; determining a cost of repair of the damaged feature of theobject based upon the nature and extent of the damage; generating aclaim form including the determined cost of repair; and displaying thegenerated claim form to a user of the structural analysis computingdevice for review and approval by the user.
 10. The computer-implementedmethod of claim 9, wherein the structural analysis computing device isintegral to the drone.
 11. The computer-implemented method of claim 9further comprising transmitting the 3D image of the object to aninsurance server.
 12. The computer-implemented method of claim 9,wherein the object sensor is configured to capture the 3D imageincluding an exterior of the object.
 13. The computer-implemented methodof claim 9, wherein the nature of the damage includes at least one offire, smoke, water, hail, wind, and theft.
 14. The computer-implementedmethod of claim 9, wherein the features of the object include at leastone of a type of the object, a manufacturer of the object, and acomponent of the object, and wherein determining the cost of the repairof damaged feature comprises determining the cost of repair of thedamaged feature based upon at least one of the type and manufacturer ofthe object.
 15. The computer-implemented method of claim 9, wherein theaccessed 3D image is a post-damage 3D image, said method furthercomprising retrieving a pre-damage 3D image from the memory.
 16. Thecomputer-implemented method of claim 15 further comprising comparing thepost-damage 3D image to the pre-damage 3D image to determine the extentof the damage to the damaged feature of the object.
 17. A mobilephotogrammetry system for generating an insurance claim associated withan object pictured in a three-dimensional (3D) image, the mobilephotogrammetry system comprising: a structural analysis computing devicecoupled to a drone, the structural analysis computing device comprising:a first memory; an object sensor configured to configured to scan aninterior structure of a room to capture the 3D image of the room,wherein the room includes a plurality of objects; at least one firstprocessor in communication with the first memory, and the object sensor,wherein the at least one first processor is programmed to: transmit aninstruction to the drone to navigate to an object of the plurality ofobjects; transmit an instruction to the object sensor to capture the 3Dimage of the object; and transmit the 3D image to an insurance server;and the insurance server comprising: a second memory; and at least onesecond processor in communication with the second memory, wherein the atleast one second processor is programmed to: receive the 3D image of theobject; analyze the 3D image captured by the drone to identify featuresof the object using image analysis trained using one or more machinelearning algorithms; automatically identify the object of the pluralityof objects within the 3D image based upon the analysis; determine thatthe identified object is an insurable asset using a database lookup ofinsurable assets; in response to determining that the identified objectis one of the insurable assets, determine a nature and an extent ofdamage to a damaged feature of the object based on the analysis;determine a cost of repair of the damaged feature of the object basedupon the nature and extent of the damage; generate a claim formincluding the determined cost of repair; and transmit the claim displaythe generated claim form to a user of the structural analysis computingdevice for review and approval by the user.
 18. The mobilephotogrammetry system of claim 17, wherein the structural analysiscomputing device is integral to the drone.
 19. The mobile photogrammetrysystem of claim 17, wherein the user computing device comprises thestructural analysis computing device.
 20. The structural analysiscomputing device of claim 1, wherein the processor is further programmedto: in response to determining the object is one of the insurableassets, identify and retrieve an insurance policy associated with theidentified object; and determine whether the insurance policy covers thedamaged feature based upon the nature and extent the damage, wherein todetermine the cost of repair of the damaged feature of the object basedupon the nature and extent of the damage, the processor is furtherprogrammed to automatically determine, when the insurance policy coversthe feature, the cost of repair of the damaged feature of the objectbased upon the nature and extent of the damage.